From a chatbot that suggests the healthiest breakfast to an algorithm that finds dangerous drug interactions, Columbia researchers are using analytics to help transform many aspects of clinical care.
Data collected by cars on driver performance—combined with machine learning—could detect elderly drivers who will soon develop mild cognitive impairment or dementia.
A new study has found that chemicals that accumulate in the vagina, potentially originating from personal care products, may contribute to preterm birth.
By applying artificial intelligence to standard-of-care imaging, Columbia cancer researchers can predict how well immunotherapy will work for patients with melanoma.
A collaboration between Observational Health Data Sciences and Informatics (OHDSI) and Health Level Seven International (HL7) will improve access and sharing of health care data among researchers.
In children with certain autism mutations, the diversity and severity of symptoms are often related to the identity and properties of gene units, called exons, targeted by the mutations.
A study of more than 1 million patients has found no increased risk of COVID-19 diagnosis, hospitalization, or complications for users of two common anti-hypertensive medications.
Researchers at Columbia, UCLA, and Northeastern have begun helping the FDA in its effort to monitor the safety and effectiveness of vaccines, including COVID-19 vaccines, and other biologic products.
Coronaviruses are adept at mimicking human immune proteins called complement, which may allow the viruses to gain a foothold in our bodies and cause disease.
With high precision, a new algorithm predicts which patients treated for traumatic injuries in the emergency department will later develop post-traumatic stress disorder.