FEATURED RESEARCH

How AI Could Spot Heart Disease Risk in Smokers Before It’s Too Late

Heart disease remains a leading cause of death worldwide, and for heavy smokers, the risk is especially pronounced.

Recent research indicates that deep learning may be key to identifying smokers at higher cardiovascular risk by focusing on changes in the aorta—the body’s largest blood vessel.

The AI advantage in aortic imaging: While coronary artery calcium (CAC) scans are traditionally used to assess cardiovascular risk, this study reveals that the aorta holds important, often overlooked indicators.

Researchers used AI to analyze aortic calcifications and volume from routine CT scans, providing a new lens on risk prediction.

As lead researcher Alexander Rau explained, “Our framework brings a fresh angle to risk prediction by focusing on thoracic aorta features, which go beyond the commonly used maximum aortic diameter.”

The numbers that matter: Among nearly 25,000 smokers in the National Lung Screening Trial, AI identified aortic calcifications and volume as stronger predictors of cardiovascular mortality than many conventional risk factors.

Those with high aortic calcification scores faced more than double the risk of cardiovascular death compared to individuals with lower scores, highlighting the potential of this approach.

A path toward personalized care: With this technology, healthcare providers could “opportunistically” utilize existing chest CT scans to identify high-risk patients, supporting preventive care with minimal added cost.

By integrating this AI-driven method into clinical workflows, we may soon see more tailored care for high-risk populations, particularly those undergoing regular lung screenings.

For more details: Full Article

Brain Booster

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Opinion and Perspectives

AI IN HEALTHCARE

Why Millions Lack Access to Life-Saving Imaging Tools

Diagnostic imaging holds immense potential to improve healthcare in low- and middle-income countries (LMICs), yet its presence in primary care is still minimal.

New research highlights the potential of tools like ultrasound and AI-assisted chest x-rays (CXR) to bridge healthcare gaps in these regions.

Barriers to access: Most primary care facilities in LMICs lack basic imaging tools.

Only 1.2% of facilities have ultrasound, with a strong need for both trained personnel and affordable equipment.

“Diagnostic imaging is essentially absent outside of hospitals,” says Madhukar Pai, Chair of Global and Public Health at McGill University, pointing to the critical gaps that patients encounter.

Imaging’s potential impact: Ultrasound and CXR could be transformative for primary care.

Portable ultrasound devices can support maternal and neonatal health, while AI-assisted CXRs have shown high accuracy in detecting tuberculosis, making them highly relevant for areas with limited healthcare access.

What needs to change: Investing in training for non-specialists and regulatory frameworks for AI-driven tools will be essential.

The authors suggest co-funding and pooled purchasing to reduce costs and improve accessibility. “With focused support,” says Pai, “imaging can strengthen primary care, bringing essential diagnostics closer to underserved populations.”

With targeted investment and policy backing, diagnostic imaging could play a vital role in enhancing care for low-resource communities.

For more details: Full Article

Top Funded Startups

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Resource: Our Startup Funding Report

Top AI Healthcare Startups of October 2024: Funding Trends and Key Players

The AI healthcare world didn’t slow down in October—it sped up. With fresh investments flooding in, October topped September’s numbers and showed us that investors are doubling down on AI’s potential in healthcare. If you thought last month was big, October said, “Hold my coffee.”

Access October’s Report: Full Report

Product Pipeline

OBESITY DRUG

New Weight Loss Drug Promises Fat Loss Without Muscle Loss

Hanmi Pharmaceutical’s HM17321 is a new obesity treatment developed with the help of AI to focus on both reducing fat and preserving muscle.

Unlike existing GLP-1 therapies, which can lead to muscle loss along with fat loss, HM17321 was precisely designed using AI to target the CRF2 receptor, achieving effective fat reduction while maintaining muscle mass.

Presented at the 2024 ObesityWeek conference, HM17321 offers a different approach to weight management by supporting muscle health, addressing a key limitation in current obesity treatments.

This AI-enhanced development process allowed Hanmi to create a more targeted and potentially effective solution for people seeking sustainable weight loss.

For more details: Full Article

Policy and Ethics

AI POLICY

Trump's Win: What It Means for the Future of AI in Healthcare

Following Trump’s 2024 election victory, AI policy in healthcare faces potential shifts. Trump has expressed plans to repeal Biden's AI Executive Order, which prioritizes safe, ethical AI development and oversight in healthcare.

This may lead to reduced federal oversight, favoring a more "free-market" approach to AI innovation, which could increase private sector autonomy but raise ethical concerns around patient safety and bias in AI tools.

With Robert F. Kennedy Jr.'s influence, skepticism toward established health agencies like the FDA may also challenge AI-based medical device approvals, impacting the pace and rigor of AI integration in clinical settings.

For more details: Full Article

Have a Great Weekend!

Trivia Answer: D) Avocado

Unlike most fruits, avocados do not ripen while still on the tree. Instead, they only begin to soften and develop their creamy texture after being harvested. This allows avocados to stay on the tree longer before picking, effectively "storing" them until needed!

ICYMI - Snapshot