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- đź‘…Can a Tongue Photo Flag Heart Disease?
đź‘…Can a Tongue Photo Flag Heart Disease?
Inside: diet-linked cancer risk, sweat biomarkers at CES, IVF AI, and faster brain mapping.

AIHealthTech Insider: Issue #82
January 5, 2026
From tongue photos that hint at heart disease, to sweat that reveals metabolic limits, to subtle cellular shifts that quietly raise cancer risk, this issue highlights how AI is uncovering early, non-obvious signals across the body. These aren’t replacements for clinicians but powerful new layers that could make screening, diagnosis, and care more proactive, accessible, and precise.
Summaries are for education, not medical advice. Always verify locally before clinical use.
A new open-access study trained AI on 12,000+ tongue images from 906 angiography patients to predict coronary artery disease using features like tongue color, fissures, coating, moisture, and red spots. The model reached up to ~80% accuracy for specific artery stenosis, suggesting a fast, non-invasive screening add-on especially in low-resource settings.

Image Source: Scientific Reports
Why it matters
Explores a low-cost, non-invasive screening signal beyond ECG and imaging
Standardizes “tongue exam” findings with computer vision instead of subjective scoring
Could enable faster triage and earlier risk detection, pending broader validation
👉 Source → AI-driven tongue image analysis for diagnosing and predicting coronary artery disease
MIT researchers found that prolonged high-fat diets push liver cells into a stem-like survival state. While this helps cells cope with chronic metabolic stress, it also strips away normal liver function, and quietly primes the tissue for cancer giving tumors a critical head start years before they appear.

Image Source: cell.com
Why it matters
Explains why fatty liver disease often precedes liver cancer
Shows how survival adaptations can unintentionally fuel tumors
Highlights new molecular targets for cancer prevention
👉 Source → https://www.cell.com/cell/fulltext/S0092-8674(25)01366-2
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Do You Know? Why Warm Hugs Feel So Good to Your Brain
New research shows that warmth and cold don’t just register on the skin -they help the brain decide whether a body feels like “mine.” Temperature signals shape body ownership, emotional regulation, and mental well-being, with disruptions linked to depression, trauma, and stroke-related body disconnect.

Image Source: cell.com
Why it matters
Shows temperature as a core signal for body awareness and emotional safety
Connects altered thermal perception to mental health and neurological conditions
Inspires sensory-based therapies and more lifelike prosthetic design
👉 Source → Shaping bodily self-awareness through thermosensory signals: Trends in Cognitive Sciences
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Researchers built SmartEM, a system that embeds machine learning inside electron microscopy scanning. It does a fast first pass, then automatically re-scans only the “hard” regions at higher quality—cutting acquisition time dramatically while preserving accuracy. Result: up to ~7× faster neural circuit mapping.

Image Source: Nature Methods
Why it matters
Makes connectomics faster without trading off reconstruction quality
Reduces wasted microscope time by focusing slow scans only where needed
Helps scale brain mapping projects that typically take months to years
👉 Source → AI-guided electron microscopy accelerates brain mapping
🩺CES 2026 Spotlight: PointFit PF-ACE
PointFit is bringing sweat intelligence to CES 2026. PF-ACE is a skin-worn sensor that reads your body through sweat - no needles, no labs, no guesswork.
The Device
A lightweight, skin-conformal sweat sensor designed for continuous, real-time biomarker tracking during training and daily activity.
Smart + Performance Features
Sweat-Based Biomarkers: Measures lactate, electrolytes, and sweat rate
Real-Time Feedback: Delivers live insights for pacing, hydration, and endurance
Non-Invasive Design: No blood, no pain, no disruption
Personalized Profiling: Supports lactate threshold–based endurance planning
Why it matters
Your sweat knows when to push—and when to back off. PF-ACE turns that signal into actionable data, helping athletes and everyday users train smarter, not harder.
👉 See PointFit at CES 2026 → Ramesh Dontha 🦉 on X
A large multicenter study shows an AI platform can automatically detect, count, and measure ovarian follicles from routine ultrasound scans during IVF. Trained on 5,500+ scans across four countries, the system matched expert sonographers while cutting annotation time by 2.5Ă—, supporting faster and more scalable fertility monitoring.

Image Source: Journal of Assisted Reproduction and Genetics
Why it matters
Delivers expert-level follicle measurements without manual workload
Reduces time and cost during ovarian stimulation monitoring
Helps standardize IVF care across clinics and ultrasound systems
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Which Biomarker Wins?

Image Source: GPT 5.2/AIHealthTech Insider
Which of these non-invasive biomarkers interests you most for clinical adoption? |
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