Unlearn

Unlearn: Advanced AI Solutions Powering the Future of Medicine

Advancing AI to power the future of medicine

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AI Directory : Healthcare

Unlearn Website screenshot

What is Unlearn?

We are advancing AI to power the future of medicine by developing and deploying AI to accelerate clinical drug development and eliminate trial and error in medicine.

How to use Unlearn?

To use our website, follow these steps: 1. Learn about digital twins and how they enhance clinical trials 2. Download our whitepaper on positioning clinical trials with digital twins for regulatory success 3. Join our team and read our publications on engineering the future of medicine with artificial intelligence

Unlearn's Core Features

TwinRCTs - Clinical trials powered by patients' digital twins

Unlearn's Use Cases

Alzheimer’s disease

Amyotrophic Lateral Sclerosis

Asthma

Atopic Dermatitis

COPD

Coronary Artery Disease

Crohn’s disease

Dyslipidemia

Frontotemporal dementia

Huntington's disease

Hypertension

Migraine

Obesity

Osteoarthritis

Osteoporosis

Parkinson's disease

Psoriasis

Psoriatic Arthritis

Rheumatoid Arthritis

SCI

Stroke

Type 2 Diabetes

Ulcerative Colitis

FAQ from Unlearn

What is Unlearn?

We are advancing AI to power the future of medicine by developing and deploying AI to accelerate clinical drug development and eliminate trial and error in medicine.

How to use Unlearn?

To use our website, follow these steps:n1. Learn about digital twins and how they enhance clinical trialsn2. Download our whitepaper on positioning clinical trials with digital twins for regulatory successn3. Join our team and read our publications on engineering the future of medicine with artificial intelligence

What are digital twins?

A patient’s digital twin is a comprehensive forecast of their future health. We invent and deploy new types of generative models trained on extensive patient-level data from previous studies.

How do digital twins enhance clinical trials?

Digital twins enhance clinical trials by calculating prognostic scores for each patient in a randomized clinical trial using their digital twins. Adjusting for these scores in the analysis increases power while adhering to guidance from regulatory agencies.

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