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Good morning! 

Welcome to Healthcare AI News, your weekly dose of the latest developments and headlines in the world of Healthcare AI.

In this issue, we explore:

✅ Headlines: From AI to Ozempic: Healthcare trends 44 leaders are watching

✅ Industry: FBI disrupts healthcare ransomware group

✅ Interesting Reads: Google’s AI, Gemini beats ChatGPT in 30 of 32 tests

✅ Tech: Walgreens’s ambitions lean on its technology. First, it has to build up its IT Department

✅ Feature: Treatment-Resistant Depression

🌟Please note that there will be no publication on Tuesday, the 26th. We will resume our regular publishing schedule on Thursday, the 28th. Wishing you all a Happy Holiday season! 🌟

HEADLINE ROUNDUP

• Using AI, MIT researchers identify a new class of antibiotic candidates (Read More)

• A high school student's award-winning algorithm: A potential game-changer for Neuralink's permanent neural implants (Read More)

• Deep learning model predicts mortality following medical procedures (Read More)

• From AI to Ozempic: The healthcare trends 44 leaders are watching (Read More)

• The brain-implant company going for neuralink’s jugular (Read More)

• VA expands access to Virtual Reality pain therapy for veterans (Read More)

• Thousands overdosed on Ozempic in 2023 (Read More)

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INDUSTRY NEWS

• Rite Aid banned from using facial recognition software after falsely identifying shoplifters (Read More)

• Philips owned BioTelemetry pays $15M for misleading clinicians (Read More)

• FBI disrupts healthcare ransomware group (Read More)

• Larry Ellison: We expect Cerner to be a growth story (Read More)

• Scientists discover new method Ebola virus uses to infect cells (Read More)

• Coronavirus subvariant JN.1 growing fast in US, already dominant in the Northeast (Read More)

• White House touts record-breaking ObamaCare enrollment (Read More)

INTERESTING READS

• OpenAI CEO Sam Altman invests $180 million in a startup looking to extend human longevity (Read More)

• Google’s AI, Gemini beats ChatGPT in 30 of 32 test categories (Read More)

• Scientists solved the nagging mystery of how genes emerge from nothing (Read More)

• Why on earth are we still using NPS? (Read More)

TECH NEWS

• How Meta built the infrastructure for Threads (Read More)

• Microsoft close to ransomware-proof glass storage, Azure users to benefit (Read More)

• Doom is 30, and so is Windows NT. How far we haven't come (Read More)

• Walgreens’s ambitions lean on its technology. First, it has to build up its IT Department (Read More)

HEALTHCARE AI JOBS

• Senior Machine Learning Engineer (LLM Digital Assistant)

• Oncology AI Solutions Lead​

• Director, Machine Learning and Data Science

THE FEATURE

Treatment-Resistant Depression

Condition spotlight: Treatment-resistant depression

At Healthcare AI News, we like to keep it light, but this week we’re spotlighting an issue that’s hard to smile at.

Treatment-resistant depression is a debilitating condition for which there are few effective remedies. (Hence the name.)

But AI is helping us get closer to an effective treatment for even this monster of a mental health condition.

Why is treatment-resistant depression so… treatment-resistant?

Treatment-resistant depression is a form of Major Depressive Disorder. A patient gets diagnosed when they don’t respond to traditional and first-line therapeutic options.

Patients might first try psychological counseling and psychiatric medication like selective serotonin reuptake inhibitors (SSRIs). 

If those methods prove unsuccessful, psychiatrists are likely to consider other pharmaceutical strategies, like the use of antipsychotics or switching antidepressants.

The next steps can involve new therapeutics like ketamine therapy or somatic therapies, like brain stimulation.

Major depression—and especially treatment-resistant depression—is no walk in the park. Studies have attributed it to significant economic burdens on society and our healthcare system. Plus, for patients, it can be incredibly debilitating—and even deadly.

How does deep brain stimulation work?

One of the somatic therapies gaining a lot of interest and traction in research on treatment-resistant depression is deep brain stimulation (DBS).

DBS works by delivering electrical impulses to the brain, often with an implanted device. This is why DBS is often referred to as a “pacemaker for the brain.”

The good news? Some patients have experienced long-term relief from their depression symptoms after undergoing DBS therapy.

But it’s not so simple.

One of the biggest challenges with using this approach to treatment-resistant depression? Depression can involve different areas of the brain for different people. And with the invasive nature of implanting a DBS device, targeting the impulses to the relevant area of the brain can be tricky.

Where does AI come in?

If you’ve been following the use of AI in mental health (we know we have), you already know it’s got so much potential for improving diagnosis and treatment.

Mental health AI tools can:

• Improve pattern recognition in diagnostic data — like CompanionMx’s voice-based depression and anxiety screening

• Speed up research for novel therapies by predicting the likelihood of success — like the Harvard Wyss Institute’s CircaVent drug discovery platform

• Personalize self-care tools — like the Woebot generative AI mental health chatbot

And when it comes to DBS therapy for treatment-resistant depression, generative AI can increase efficacy by quantifying and personalizing the approach. 

In a small study recently published in Nature, researchers gathered data from the brains of 10 subjects receiving DBS therapy for treatment-resistant depression. 

They used an explainable AI system to analyze patterns in the brain scans, finding quantifiable biomarkers to reflect the subjects’ depression.

Notably, these biomarkers are more specific than the digital biomarkers used by mental health startups like Mindstrong.

“It’s a coordination of a collection of features [that] appear to be changing together,” study co-author Christopher Rozell said. For instance, “a sick brain going to well looks like, in the left hemisphere, alpha and beta [wave] increases, and in the right, alpha and gamma increases.”

The researchers hoped to use the biomarkers to not only diagnose and track depression’s progression but to also better tailor DBS—and other types of therapies—to each individual patient.

As for the study’s patients, after 24 weeks, 90% of participants had a significant clinical response to the DBS treatment and 70% even achieved remission. 

But what we think is even more promising is that, when a subject experienced a relapse months later, the AI detected an indicator of relapse five weeks before it happened. 

This kind of data can help clinicians distinguish between a true risk for relapse versus a patient having a more benign, brief low period. That kind of information is gold for providers who often don’t have much more to go off of than very subjective psychological questionnaires.

Final thoughts from HAN

DBS is still an exploratory therapy for treatment-resistant depression. It’s not widely available to patients (yet).

Patients deserve more than the hopelessness they face with a treatment-resistant depression diagnosis. We hope AI can be part of getting them their much-needed answers and progress.

We want to hear from you: Which other conditions should we spotlight? Reply to this email to let us know.

And if you’re struggling with depression, please know that you’re not alone. There are ways to get better. 

Reach out to SAMHSA’s National Helpline to learn more about mental health options. 

And if you or someone you know is in crisis, call or text 988.

TWEET OF THE WEEK

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