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health 10

AI health tools use machine learning to support medical documentation, patient monitoring, mental wellness, fitness tracking, and symptom assessment. This category includes 68 tools used by healthcare providers, clinics, and individuals managing their own wellbeing. They cover a wide range from clinical-grade documentation assistants to consumer apps for stress and habit tracking.

Lyrebird Health

health

AI scribe for clinical note-taking during consultations

Paid 41 · 43,247 votes

AI Skin scanner & mole checker

health

AI skin health diagnostic app for self-monitoring

Paid 41 · 63,626 votes

Lunit

health

AI imaging and analysis software for cancer detection and treatment

Paid 38 · 23,332 votes

Vital

health

Personalized guided meditation and mental support

Paid 37 · 45,295 votes

Deepwander

health

AI introspection for self-awareness and values alignment

Paid 37 · 36,875 votes

Scribeberry

health

AI medical scribe for clinical documentation

Paid 37 · 33,024 votes

Supafit

health

AI-generated workout plans tailored to your fitness level

Paid 36 · 32,579 votes

TherapyWithAI

health

Private AI mental health support anytime

Paid 36 · 30,510 votes

Thumos Care

health

Personalized mental wellness support

Paid 36 · 27,405 votes

Journable

health

Track calories and exercise through conversation

Paid 35 · 13,235 votes

The tools here split between clinical and consumer contexts, and that distinction matters when evaluating them. Clinical tools, such as SOAP note generators for practitioners or maternal health monitoring platforms, are subject to healthcare regulations that vary by country, including HIPAA in the US. Buyers in those contexts should verify compliance certifications before processing any patient data. Consumer wellness tools are less regulated but vary widely in the quality of their guidance, some are backed by licensed professionals, others rely entirely on AI-generated responses. For mental health apps in particular, check whether there is a human escalation path for users in distress. Pricing models range from free apps with limited features to per-seat enterprise subscriptions for clinical teams. When assessing any health AI tool, the most important questions are: what data it collects, how it stores it, whether outputs are reviewed by qualified humans, and what liability the provider accepts. This is not a category where choosing based on pricing alone is advisable.