The healthcare system is faced with a tsunami of incoming data. In fact, the average hospital produces roughly 50 petabytes of data every year. That’s more than twice the amount of data housed in the ...
Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
Version 1 of the SPARK platform was released to pilot users, who represented diverse end users, including molecular biologists, clinicians, and bioinformaticians. Included in the pilot release of ...
The proposed blockchain model reflects a broader movement in global healthcare toward giving patients greater authority over ...
PhD, MBA, CTO at John Snow Labs. Making AI & NLP solve real-world problems in healthcare, life science and related fields. Artificial intelligence (AI) and machine learning applications are widely ...
A recent Npj Digital Medicine study evaluated the effectiveness of COMPOSER, a deep learning model for early sepsis prediction. It assessed the impact of this model on the quality of patient care and ...
Meeting patients’ needs—inside and outside the clinic walls—is essential to help ensure patients with cancer achieve optimal outcomes. Socioeconomic and environmental insecurities make it more ...
In a recent study published in the journal Informatics, researchers investigated the use of advanced machine learning methods to recognize facial expressions as indicators of health deterioration in ...
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