#NIGHTINGALE OPEN 40TB FINANCIALTIMES FREE#

How does Nightingale fill gaps in existing medical datasets? It also accelerates Artificial Intelligence in the field of health sciences by collecting, vetting, and cleaning the data, making it exceptionally high-quality.

#NIGHTINGALE OPEN 40TB FINANCIALTIMES FREE#

It shares de-identified clinical datasets with the researchers, absolutely free of cost. Nightingale Open Science is an endeavor to help researchers, startups, and anyone who has to work extremely hard to access high-quality medical data. How does Nightingale’s Open Science make things easier for researchers? They have to deal with several challenges in the middle, including – getting themselves into the hospital system to access the data and wasting several months in the process. But what about other people and enterprises that cannot pay large sums to access medical data? They end up wasting several days and even months negotiating for access to data. The other part is owned by big tech companies that can spend large amounts to access the data. Some part of carefully examined, high-quality data is primarily owned by medical institutions that reserve access to this data to their own researchers. The current medical data is often siloed. Problems with the current landscape of the medical data The project has already started garnering attention from tech giants like Google and hundreds of researchers from institutions like MIT, Berkeley, Cornell, Stanford, and the University of Chicago. This gives researchers the ability to learn from the ground truth, which is the actual patient outcomes. How are these datasets different and more valuable?Īs per Ziad Obermeyer, the physician and Machine Learning scientist who launched Nightingale Open Science, what sets these datasets apart from the rest is the fact they are not labeled with the doctor’s opinion but with what actually happened to the patient.įor example, cardiac arrest ECG datasets will not be labeled with whether cardiologists detected something wrong with the patient but whether the patient eventually suffered a cardiac arrest. and Taiwan and will soon be expanded to Kenya and Lebanon to include medical diversity. The datasets have been built over two years in the U.S.

The images are also labeled with the medical outcomes, such as the severity of Covid-19 disease and whether the Covid patient needed a ventilator. The data include 40TB of medical imagery, such as electrocardiogram waveforms, X-rays, and pathology specimens, from patients with different conditions, including sudden cardiac arrest, high-risk breast cancer, Covid-19, maternal mortality, etc. It could help train AI to predict medical conditions earlier and save lives, benefitting the patients and enhancing the utility of AI for clinicians. Recently, Nightingale Open Science, an open-source platform containing advanced, de-identified medical datasets, has made 40 terabytes of medical data widely available for researchers for free. Data is a crucial resource for most medical and health research.

Nightingale open 40tb financialtimes