Americans and Western nation citizens have record levels of chronic diseases. Obesity is epidemic. Cardiovascular disease still kills more Americans than any other cause. Cancer is striking ever younger people.
Modern medicine has been reactive. After a patient gets sick, a doctor evaluates symptoms, diagnoses the illness and proposes generic therapies.
The American medical system spends far more money on healthcare yet obtains the worst outcomes.
The old medical paradigm is relatively inefficient, inequitable and unproductive.
New technologies enable medicine to be information-rich, predictive and tailored to each individual.
Several concurrent revolutions converge on a new kind of medicine. Genomics and proteomics enable analysis of patient molecular data. Computational analytics enables a new generation of bioinformatics. Artificial intelligence provides powerful tools for medical data analysis.
21st century technologies provide solutions for a new paradigm in medicine.
In the new paradigm for medicine, medical modeling is the centerpiece of the physician's practice.
Medical modeling—sometimes called medical digital twins—allows identification of solutions to each patient's unique health challenges.
When a patient gets sick, a physician diagnoses the illness with greater precision from the patient's genetic and biomarker data.
Precision molecular data inform individualized medical models that analyze and diagnose a patient's illness.
Once a disease is precisely identified, medical modeling is applied—typically by specialists—to identify therapeutic solution options.
Therapies are tailored to each unique patient illness.
In some cases, a novel therapy is developed to solve a complex patient disease by applying a new generation of analytics.
Medical modeling is applied to predicting disease prognosis.
Diseases that have no cure are modeled to predict the evolution of the disease progress. For example, the progress of degenerative diseases can be probabilistically predicted.
When a therapy is provided, modeling is applied to predict the various scenarios of the disease management.
Modeling therapies enable adaptation of the treatment options with new information.
AI and computational analysis are applied to medical modeling.
Generative AI (GenAI), machine learning (ML) and deep learning (DL) techniques are applied to medical data analysis.
The evaluation of each individual's medical data is compared to medical databases in order to evaluate each patient's specific pathologies.
AI is applied to ID therapy options, including novel therapies for each patient.
AI is also applied to the prediction of disease progress with and without therapeutic applications.
Gemini serves medical doctors and researchers. One focus remains on chronic diseases addressed by internists, cardiologists, oncologists, neurologists and immunologists. The following medical specialties are illustrative of our customers.
Gemini supports specialty-focused medical modeling and analysis workflows designed to improve diagnostic precision, scenario-based prognostics and personalized therapeutics.
Join physicians and researchers using Gemini to transform patient care through AI-driven digital twins.
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