What Key Laboratory Leaders Will Learn at This Week’s 2023 Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management

Executives and pathologists from many of the nation’s most prominent clinical laboratories are on their way to the Crescent City today to share best practices, hear case studies from innovative labs, and network

NEW ORLEANS—This afternoon, more than 900 lab CEOs, administrators, and pathologists will convene for the 28th Annual Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management conference. Three topics of great interest will center around adequate lab staffing, effective cost management, and developing new sources of lab testing revenue.

Important sessions will also address the explosion in next-generation sequencing and genetic testing, proposed FDA regulation of laboratory-developed tests (LDTs), and innovative ways that clinical laboratories and pathology groups can add value and be paid for that additional value.

All this is happening amidst important changes to healthcare and medicine in the United States. “Today, the US healthcare system is transforming itself at a steady pace,” explained Robert L. Michel, Editor-in-Chief of The Dark Report and Founder of the Executive War College. “Big multi-hospital health systems are merging with each other, and payers are slashing reimbursement for many medical lab tests, even as healthcare consumers want direct access to clinical laboratory tests and the full record of their lab test history.

“Each of these developments has major implications in how clinical laboratories serve their parent organizations, offer services directly to consumers, and negotiate with payers for fair reimbursement as in-network providers,” Michel added. “Attending the Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management equips lab leaders with the tools they’ll need to make smart decisions during these challenging times.”

Executive War College

Now in its 28th year, the Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management convenes April 25-26 in New Orleans. Executive War College extends to a third day with three full-day workshops: LEAN fundamentals for lab leaders, a genetic testing program track, and a digital pathology track. Learn more at www.ExecutiveWarCollege.com. (Photo copyright: The Dark Intelligence Group.)

Challenges and Opportunities for Clinical Laboratories

With major changes unfolding in the delivery and reimbursement of clinical services, clinical laboratory and pathology practice leaders need effective ways to respond to the evolving needs of physicians, patients, and payers. As The Dark Report has often covered, three overlapping areas are a source of tension and financial pressure for labs:

  • Day-to-day pressures to manage costs in the clinical laboratory or pathology practice.
  • The growing demand for genetic testing, accompanied by reimbursement challenges.
  • Evolving consumer expectations in how they receive medical care and interact with providers.

Addressing all three issues and much more, the 2023 Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management features more than 80 sessions with up to 125 lab managers, consultants, vendors, and in vitro diagnostic (IVD) experts as speakers and panelists.

Old-School Lab Rules Have Evolved into New-School Lab Rules

Tuesday’s keynote general sessions (to be reported exclusively in Wednesday’s Dark Daily ebriefing) will include four points of interest for clinical laboratory and pathology leaders who are managing change and pursuing new opportunities:

  • Positioning the lab to prosper by serving healthcare’s new consumers, new care models, new payment models, and more, with Michel at the podium.
  • How old-school lab rules have evolved into new-school lab rules and ways to transition the lab through today’s disrupters in healthcare and the clinical laboratory marketplace, with Stan Schofield, Managing Principal of the Compass Group.
  • The growing trend of clinical laboratory-pharmacy relationships with David Pope, PharmD, CDE, Chief Pharmacy Officer at OmniSYS, XIFIN Pharmacy Solutions.
  • Generating value by identifying risk signals in longitudinal lab data and opportunities in big data from payers, physicians, pharma, and bioresearch, with Brad Bostic, Chairman and CEO of hc1.

Wednesday’s keynote sessions (see exclusive insights in Friday’s Dark Daily ebriefing) explore:

Wednesday’s keynotes conclude with a panel discussion on delivering value to physicians, patients, and payers with lab testing services.

Clinical Labs, Payers, and Health Plans Swamped by Genetic Test Claims

Attendees of the 2023 Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management may notice a greater emphasis on whole genome sequencing and genetic testing this year.

As regular coverage and analysis in The Dark Report has pointed out, clinical laboratories, payers, and health plans face challenges with the explosion of genetic testing. Several Executive War College Master Classes will explore critical management issues of genetic and genomic testing, including laboratory benefit management programs, coverage decisions, payer relations, and best coding practices, as well as genetic test stewardship.

This year’s Executive War College also devotes a one-day intensive session on how community hospitals and local labs can set up and offer genetic tests and next-generation sequencing services. This third-day track features more than a dozen experts including:

During these sessions, attendees will be introduced to “dry labs” and “virtual CLIA labs.” These new terms differentiate the two organizations that process genetic data generated by “wet labs,” annotate it, and provide analysis and interpretation for referring physicians.

State of the Industry: Clinical Lab, Private Practice Pathology, Genetic Testing, IVD, and More

For lab consultants, executives, and directors interested in state-of-the-industry Q/A and discussions concerning commercial laboratories, private-practice pathology, and in vitro diagnostics companies, a range of breakout sessions, panels, and roundtables will cover:

  • Action steps to protect pathologists’ income and boost practice revenue.
  • Important developments in laboratory legal, regulatory, and compliance requirements.
  • New developments in clinical laboratory certification and accreditation, including the most common deficiencies and how to reach “assessment ready” status.
  • An update on the IVD industry and what’s working in today’s post-pandemic market for lab vendors and their customers.
  • Federal government updates on issues of concern to clinical laboratories, including PAMA, the VALID Act, and more.

Long-time attendees will notice the inclusion of “Diagnostics” into the Executive War College moniker. It’s an important addition, Michel explained for Dark Daily.

“In the recent past, ‘clinical laboratory’ and ‘anatomic pathology’ were terms that sufficiently described the profession of laboratory medicine,” he noted. “However, a subtle but significant change has occurred in recent years. The term ‘diagnostics’ has become a common description for medical testing, along with other diagnostic areas such as radiology and imaging.”

Key managers of medical laboratories, pathology groups, and in vitro diagnostics have much to gain from attending the Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management, now in its 28th year. Look for continued coverage through social media channels, at Dark Daily, and in The Dark Report.

Clinical laboratories are invited to continue the conversations by joining the Executive War College Discussion Group and The Dark Report Discussion Group on LinkedIn.

Liz Carey

Related Information:

Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management Agenda

Six Important Themes to Help Labs Succeed

Executive War College Press

The Dark Report

Dark Daily eBriefings

The Dark Report Discussion Group

Executive War College Discussion Group

Vanderbilt University Researchers Combine Genetic Data and EHR Records to Identify Undiagnosed Disease in Patients

Multi-university research group discovers that heart arrhythmia genes may be more common than previously thought

For years, big data has been heralded as the key to unlocking the promise of personalized medicine. Now, researchers at Vanderbilt University are bringing that goal a step closer to reality by combining genetic testing data with data stored in electronic health record (EHR) systems to reveal undiagnosed disease in individual patients.

Should their research result in new ways to identify and diagnose disease, doctors and clinical laboratories would do confirmatory testing and then initiate a precision medicine plan.

Vanderbilt University Medical Center (VUMC) led a multi-university team of researchers that used data from the eMERGE (Electronic Medical Records and Genomics) network in two separate studies. eMERGE is a consortium of medical centers funded by the National Human Genome Research Institute (NHGRI) for the advancement of EHR data in genomics research.

The first study, published in the journal Circulation, titled, “Arrhythmia Variant Associations and Reclassifications in the eMERGE-III Sequencing Study,” looked at 10 arrhythmia-associated genes in individuals who had no prior indication for cardiac genetic testing.

The second study, published in Jama Oncology, titled, “Association of Pathogenic Variants in Hereditary Cancer Genes with Multiple Diseases,” explored the spectrum of diseases associated with hereditary cancer genes.

Dan Roden, MD, Senior Vice President for Personalized Medicine at VUMC and Senior Author of the Circulation study, said in a VUMC news release that the findings support the growing use of genetic information in clinical care.

“The questions we asked were: How many people who had no previous indication for cardiac genetic testing had pathogenic or likely pathogenic variants, and how many of those people actually had a phenotype in the electronic health records?” he explained.

Arrhythmia More Common than Previously Thought

The VUMC researchers drew data for their reports from the eMERGE Phase III study, which investigated the feasibility of population genomic screening by sequencing 109 genes across the spectrum of Mendelian diseases—genetic diseases that are caused by a mutation in a single gene—in more than 20,000 individuals. The scientists returned variant results to the participants and used EHR and follow-up clinical data to ascertain patient phenotypes, according to a Northwestern University Feinberg School of Medicine news release.

The research team looked specifically at the 120 consortium participants that had disease-associated pathogenic or likely pathogenic (P/LP) variants in the arrhythmia-associated genes. An analysis of the EHR data showed that 0.6% of the studied population had a variant that increases risk for potentially life-threatening arrhythmia, and that there was overrepresentation of arrhythmia phenotypes among patients, the VUMC news release noted.

The research team returned results to 54 participants and, with clinical follow-up, made 19 diagnoses (primarily long-QT syndrome) of inherited arrhythmia syndromes. Twelve of those 19 diagnoses were made only after variant results were returned, the study’s authors wrote.

Carlos G. Vanoye, PhD, Research Associate Professor of Pharmacology at Northwestern University (NU), said the study suggests arrhythmia genes may be more common than previously thought.

“A person can carry a disease-causing gene variant but exhibit no obvious signs or symptoms of the disease,” he said in the NU news release. “Because the genes we studied are associated with sudden death, which may have no warning signs, discovery of a potentially life-threatening arrhythmia gene variant can prompt additional clinical work-up to determine risks and guide preventive therapies.”

Dan Roden, MD

“The take-home message is that 3% of people will carry a pathogenic or likely pathogenic variant in a disease-causing gene and many others will carry variants of uncertain significance,” said Dan Roden, MD (above), Senior Vice President for Personalized Medicine at VUMC and Senior Author of the Circulation study in the VUMC news release. “We can use genetic testing, electronic health record phenotypes, and in vitro technologies to evaluate and find people who have unrecognized genetic disease and save lives by making earlier diagnoses.” Clinical laboratories will play a key role in making those early diagnoses and in managing personalized medical treatment plans. (Photo copyright: Vanderbilt University.)

Variants of Uncertain Significance

According to the NU news release, the scientists determined the functional consequences of the variants of uncertain significance they found and used that data to refine the assessment of pathogenicity. In the end, they reclassified 11 of the variants: three that were likely benign and eight that were likely pathogenic.

In the JAMA Oncology study, the VUMC scientists and other researchers conducted a phenome-wide association study to find EHR phenotypes associated with variants in 23 hereditary cancer genes. According to the VUMC news release, they identified 19 new associations:

The VUMC study findings could improve disease diagnosis and management for cancer patients and help identify high-risk individuals, the researchers noted in their published report.

Other Scientists Urge Caution

Nonetheless, Amsterdam University Medical Centers professors Roddy Walsh, PhD,  Connie Bezzina, PhD, and Arthur A.M. Wilde, PhD, urged caution with coupling large-scale genomic analysis to EHRs.

In an editorial published in Circulation, titled, “First Steps of Population Genomic Medicine in the Arrhythmia World: Pros and Cons,” the professors noted that using genomic information in the case of potentially lethal inherited arrhythmia syndromes could be “lifesaving,” but questioned the benefits of reporting such secondary findings when patients are undergoing genome sequencing for other indications such as cancer.

“The likelihood that these ‘genetic diagnoses’ are translated into clinical diagnoses have not been completely evaluated,” they wrote. “In addition to the challenge of accurately identifying disease-causing genetic variants, defining the penetrance of such variants is critical to this process, i.e., what proportion of individuals in the general population with apparently pathogenic variants will develop the associated phenotype? If penetrance is low for particular gene/phenotype combinations, the costs associated with clinical screening and the psychological effects on individuals informed that they have potentially life-threatening variants may outweigh the benefits of the few new clinical diagnoses.”

These latest studies provide further evidence of the value of big data in healthcare and offer another lesson to clinical laboratories and pathologist about the future role data streaming from clinical laboratories and pathology assays may have in the growth of personalized medicine. 

—Andrea Downing Peck

Related Information:

Studies Combine Genetic Testing, Electronic Health Records to Find Undiagnosed Diseases

Arrhythmia Variant Associations and Reclassifications in the eMERGE-III Sequencing Study

Electronic Medical Records and Genomics (eMERGE) Phase III (eMERGE)

First Steps of Population Genomic Medicine in the Arrhythmia World: Pros and Cons

Association of Pathogenic Variants in Hereditary Cancer Genes with Multiple Diseases

Arrhythmia Genes More Common than Previously Thought

Adolescents with Specific Health Conditions Experience Accelerated Aging at Midlife, According to Published Study in New Zealand

Study shows that access to early childhood treatment could have lasting effects and prevent premature adult aging

Researchers in New Zealand have found that people who experienced “daily smoking status, obesity, or a psychological disorder diagnosis” beginning early in life were “biologically older” at midlife than those who did not. The findings suggest that early access to treatments for these health concerns could decrease risk for “accelerated biological aging,” according to the study published in JAMA Pediatrics.

Although these findings do not currently provide a path to a diagnostic test for clinical laboratories, this study is yet another example of how researchers are increasingly using broad swaths of healthcare data to help identify people at risk for certain healthcare conditions.

Such research often presents opportunities for medical laboratories to participate in healthcare Big Data analysis, which in turn helps healthcare providers make precision medicine diagnoses for individual patients.

Study Assessments and Clinical Laboratory Biomarkers

Researchers from the Dunedin Multidisciplinary Health and Development Research Unit (DMHDRU) at University of Otago analyzed the health and behaviors of 910 people (54% men, 46% women) born in Dunedin, New Zealand, between April 1, 1972, and March 31, 1973, through age 45.

The scientists found that participants who had one of three health conditions as an adolescent—obesity, smoking daily, or psychological disorder (anxiety, attention deficit/hyperactivity disorder, depression)—showed advanced signs of aging at age 45 when compared to others without those conditions, CNN reported.

The signs included:

  • Walking 11.2 centimeters per second slower.
  • Brain appears 2.5 years older.
  • Face appears four years older.

At age 11, 13, and 15, the Dunedin Study participants were assessed by pulmonary specialists and others for asthma, cigarette smoking, and obesity, Fox News reported.

Kyle Bourassa, PhD
“There’s a long history of that kind of research in terms of how smoking is damaging at the cellular level but also can result in the kinds of health conditions that we associate with biological aging, like (chronic obstructive pulmonary disease), lung cancer, things like that,” the study’s first author Kyle Bourassa, PhD (above), told CNN. “The hope is if we were to study a cohort now, a much higher proportion of those children and adolescents are actually going to be treated for these things, which will reduce the risk of accelerated aging later in life,” he added. Results of the study may also lead to new clinical laboratory diagnostics. (Photo copyright: Duke University.)

According to an earlier DMHDRU statement, the biomarkers used at this point in the study included:

The researchers also tracked asthma’s effects but concluded it did not contribute to aging, probably due to availability of asthma treatments, the authors wrote in their study published in JAMA Pediatrics, titled, “Association of Treatable Health Conditions During Adolescence with Accelerated Aging at Midlife.”

“Participants who had smoked daily, had obesity, or had a psychological disorder diagnosis during adolescence were biologically older at midlife compared with participants without these conditions. Participants with asthma were not biologically older at midlife compared with those without asthma,” the researchers wrote. These findings led the researchers to certain conclusions about receiving early treatments, CNN reported.

“No participants in this cohort were prescribed stimulants for attention-deficit/hyperactivity disorder, and selective serotonin reuptake inhibitors were not yet in use for adolescent depression and anxiety during the study period. Whereas 81.1% of the adolescents with asthma received some type of treatment, which could have mitigated the implications for biological aging,” the authors wrote in their study.

“Our paper reaffirms that those are important treatments and those kinds of investments younger in the lifespan could net big benefits in terms of both health and the cost of healthcare later on as well,” Kyle Bourassa, PhD, told CNN. Bourassa is the study’s First Author and a clinical psychology researcher and advanced research fellow at the Durham VA Health Care System.

Clinical Laboratories Curate Massive Amounts of Healthcare Data

For pathologists and medical laboratory scientists, the University of Otago study is a reminder that clinical laboratories provide a critical tool to diagnostics professionals: housing, sharing, and analyzing data that contribute to precision medicine diagnoses.

The DMHDRU researchers’ findings also highlight the importance of access to common treatments offered early in life for some people to reduce risk of accelerated aging and disease.

Donna Marie Pocius

Related Information:

Association of Treatable Health Conditions During Adolescence with Accelerated Aging at Midlife

Having Certain Health Conditions in Adolescence May Be Linked with Faster Aging in Adulthood, Study Says

Aging Faster in Adulthood Linked to Health Conditions in Adolescence

UK Researchers Discover Previously Unknown ‘Highly Virulent’ HIV Variant Circulating in Netherlands since 1990s

Though the variant poses low risk thanks to modern HIV treatments, the scientists stress the importance of access to early clinical laboratory testing for at-risk individuals

With the global healthcare industry hyper focused on arrival of the next SARS-CoV-2 variant, pathologists and clinical laboratories may be relieved to learn that—though researchers in the Netherlands discovered a previously unknown “highly virulent” strain of HIV—the lead scientist of the study says there’s “no cause for alarm.”

In a news release, researchers at the University of Oxford Big Data Institute said the HIV variant got started in the Netherlands in the 1990s, spread quickly into the 2000s, and that prior to treatment, people with the new virulent subtype B (VB variant) had exceptionally high viral loads compared to people with other HIV variants.

Fortunately, the scientist also found that around 2010, thanks to antiretroviral drug therapy, the severe variant began to decline.

The scientists published their findings in the peer-reviewed journal Science, titled, “A Highly Virulent Variant of HIV-1 Circulating in the Netherlands.”

‘Nobody Should Be Alarmed’

In an interview with NPR, Chris Wymant, PhD, the study’s lead author, said, “People with this variant have a viral load that is three to four times higher than usual for those with HIV. This characteristic means the virus progresses into serious illness twice as fast, and also makes it more contagious.”

Fortunately, he added, “Existing medications work very well to treat even very virulent variants like this one, cutting down on transmission and reducing the chance of developing severe illness.

“Nobody should be alarmed,” he continued. “It responds exactly as well to treatment as HIV normally does. There’s no need to develop special treatments for this variant.”

Wymant is senior researcher in statistical genetics and pathogen dynamics at the Big Data Institute (BDI).

Chris Wymant, PhD
Epidemiologist Chris Wymant, PhD (above), lead author of the Big Data Institute study at Oxford University, says today’s modern HIV antiretroviral drug therapies effectively treat for the “highly viral” HIV VB variant he and his team discovered. “Nobody should be alarmed,” he told NPR. “It responds exactly as well to treatment as HIV normally does.” Nevertheless, he stressed the importance of access to early clinical laboratory testing for at-risk individuals. (Photo copyright: Oxford Big Data Institute.)

Genetic Sequences of the Virulent Virus

About 680,000 people worldwide died from AIDS in 2020, down from 1.3 million in 2010, according to US Health and Human Services HIV data.

In their published study, the BDI researchers reported that their analysis of genetic sequences of the VB variant suggested it “arose in the 1990s from de novo (of new) mutation, not recombination, with increased transmissibility and an unfamiliar molecular mechanism of virulence.

“By the time, they were diagnosed, these individuals were vulnerable to developing AIDS within two to three years. The virus lineage, which has apparently arisen de novo since around the millennium, shows extensive change across the genome affecting almost 300 amino acids, which makes it hard to discern the mechanism for elevated virulence,” the researchers noted.

The researchers analyzed a data set from the project BEEHIVE (Bridging the Epidemiology and Evolution of HIV in Europe and Uganda). They found 15 of 17 people positive for the VB variant residing in the Netherlands. That prompted them to focus on a cohort of more than 6,700 Dutch HIV positive people in the ATHENA (AIDS Therapy Evaluation in the Netherlands) cohort database, where they found 92 more individuals with the VB variant, bringing the total to 109.

According to a Medscape report on the study’s findings, people with the VB variant showed the following characteristics:

  • Double the rate of CD4-positive T-cell declines (indicator of immune system damage by HIV), compared to others with subtype-B strains.
  • Increased risk of infecting others with the virus based on transmissibility associated with variant branching.

Wymant says access to clinical laboratory testing is key to curtailing the number of people who contract the VB variant. “Getting people tested as soon as possible, getting them onto treatment as soon as possible, has helped reduce the numbers of this variant even though we didn’t know that it existed,” he told NPR.

The University of Oxford Big Data Institute study is another example of how constantly improving genome sequencing technology allows scientists to dig deeper into genetic material for insights that can advance the understanding of many diseases and health conditions.

Donna Marie Pocius

Related Information:

New Highly Virulent and Damaging HIV Variant Discovered in the Netherlands

Highly Virulent Variant of HIV-1 Circulating in the Netherlands

Discovery of HIV Variant Shows Virus Can Evolve to Be More Severe and Contagious

Highly Virulent Form of the HIV-1 Virus Has Been Discovered in the Netherlands by an International Collaboration Led by Researchers of Oxford Big Data Institute

What is Swarm Learning and Might It Come to a Clinical Laboratory Near You?

International research team that developed swarm learning believe it could ‘significantly promote and accelerate collaboration and information exchange in research, especially in the field of medicine’

Swarm Learning” is a technology that enables cross-site analysis of population health data while maintaining patient privacy protocols to generate improvements in precision medicine. That’s the goal described by an international team of scientists who used this approach to develop artificial intelligence (AI) algorithms that seek out and identify lung disease, blood cancer, and COVID-19 data stored in disparate databases.

Since 80% of patient records feature clinical laboratory test results, there’s no doubt this protected health information (PHI) would be curated by the swarm learning algorithms. 

Researchers with DZNE (German Center for Neurodegenerative Diseases), the University of Bonn, and Hewlett Packard Enterprise (HPE) who developed the swarm learning algorithms published their findings in the journal Nature, titled, “Swarm Learning for Decentralized and Confidential Clinical Machine Learning.”

In their study they wrote, “Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. … However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking, and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning.”

What is Swarm Learning?

Swarm Learning is a way to collaborate and share medical research toward a goal of advancing precision medicine, the researchers stated.

The technology blends AI with blockchain-based peer-to-peer networking to create information exchange across a network, the DZNE news release explained. The machine learning algorithms are “trained” to detect data patterns “and recognize the learned patterns in other data as well,” the news release noted. 

Joachim Schultze, MD

“Medical research data are a treasure. They can play a decisive role in developing personalized therapies that are tailored to each individual more precisely than conventional treatments,” said Joachim Schultze, MD (above), Director, Systems Medicine at DZNE and Professor, Life and Medical Sciences Institute at the University of Bonn, in the news release. “It’s critical for science to be able to use such data as comprehensively and from as many sources as possible,” he added. This, of course, would include clinical laboratory test results data. (Photo copyright: University of Bonn.)
 

Since, as Dark Daily has reported many times, clinical laboratory test data comprises as much as 80% of patients’ medical records, such a treasure trove of information will most likely include medical laboratory test data as well as reports on patient diagnoses, demographics, and medical history. Swarm learning incorporating laboratory test results may inform medical researchers in their population health analyses.

“The key is that all participants can learn from each other without the need of sharing confidential information,” said Eng Lim Goh, PhD, Senior Vice President and Chief Technology Officer for AI at Hewlett Packard Enterprise (HPE), which developed base technology for swarm learning, according to the news release.

An HPE blog post notes that “Using swarm learning, the hospital can combine its data with that of hospitals serving different demographics in other regions and then use a private blockchain to learn from a global average, or parameter, of results—without sharing actual patient information.

“Under this model,” the blog continues, “‘each hospital is able to predict, with accuracy and with reduced bias, as though [it has] collected all the patient data globally in one place and learned from it,’ Goh says.”

Swarm Learning Applied in Study

The researchers studied four infectious and non-infectious diseases:

They used 16,400 transcriptomes from 127 clinical studies and assessed 95,000 X-ray images.

  • Data for transcriptomes were distributed over three to 32 blockchain nodes and across three nodes for X-rays.
  • The researchers “fed their algorithms with subsets of the respective data set” (such as those coming from people with disease versus healthy individuals), the news release noted.

Findings included:

  • 90% algorithm accuracy in reporting on healthy people versus those diagnosed with diseases for transcriptomes.
  • 76% to 86% algorithm accuracy in reporting of X-ray data.
  • Methodology worked best for leukemia.
  • Accuracy also was “very high” for tuberculosis and COVID-19.
  • X-ray data accuracy rate was lower, researchers said, due to less available data or image quality.

“Our study thus proves that swarm learning can be successfully applied to very different data. In principle, this applies to any type of information for which pattern recognition by means of artificial intelligence is useful. Be it genome data, X-ray images, data from brain imaging, or other complex data,” Schultze said in the DZNE news release.

The researchers plan to conduct additional studies aimed at exploring swarm learning’s implications to Alzheimer’s disease and other neurodegenerative diseases.

Is Swarm Learning Coming to Your Lab?

The scientists say hospitals as well as research institutions may join or form swarms. So, hospital-based medical laboratory leaders and pathology groups may have an opportunity to contribute to swarm learning. According to Schultze, sharing information can go a long way toward “making the wealth of experience in medicine more accessible worldwide.”

Donna Marie Pocius

Related Information:

AI With Swarm Intelligence: A Novel Technology for Cooperative Analysis of Big Data

Swarm Learning for Decentralized and Confidential Clinical Machine Learning

Swarm Learning

HPE’s Dr. Goh on Harnessing the Power of Swarm Learning

Swarm Learning: This Artificial Intelligence Can Detect COVID-19, Other Diseases

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