Machine Learning Is Enabling A New Era For Precision Medicine And Pharmacogenomics

Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...

Hospital AI tool predicts low blood sugar in patients up to 24 hours in advance

Cedars-Sinai Health Sciences University investigators developed an AI-based model that can identify hospitalized patients at ...
VentureBeat

Beyond the lakehouse: Fundamental's NEXUS bypasses manual ETL with a native foundation model for tabular data

The deep learning revolution has a curious blind spot: the spreadsheet. While Large Language Models (LLMs) have mastered the nuances of human prose and image generators have conquered the digital ...
Nature

Pediatric diabetes prediction using machine learning

Diabetes is a chronic condition that affects a substantial portion of the global population and is linked to elevated mortality rates and a range of severe health complications. Despite its clinical ...
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Machine Learning Can Predict Intradialytic Hypotension During Hemodialysis

WEDNESDAY, Nov. 6, 2024 (HealthDay News) -- Clinical data and machine learning can help to predict intradialytic hypotension (IDH) for patients undergoing hemodialysis, according to a study published ...
Frontiers

Machine learning-based prediction of diabetic peripheral neuropathy: model development and clinical validation

Diabetic peripheral neuropathy (DPN) is a common and debilitating complication of type 2 diabetes mellitus (T2DM), significantly impacting patients’ quality of life and increasing healthcare burdens.
ahajournals.org

Artificial Intelligence and Machine Learning in Preeclampsia

Preeclampsia is a multisystem hypertensive disorder that manifests itself after 20 weeks of pregnancy, along with proteinuria. The pathophysiology of preeclampsia is incompletely understood.
Scientific Research Publishing

Optimizing Healthcare Outcomes through Data-Driven Predictive Modeling ()

This study investigates the transformative potential of big data analytics in healthcare, focusing on its application for forecasting patient outcomes and enhancing clinical decision-making. The ...
Nature

Predicting severe intraventricular hemorrhage or early death using machine learning algorithms in VLBWI of the Korean Neonatal Network Database

Severe intraventricular hemorrhage (IVH) in premature infants can lead to serious neurological complications. This retrospective cohort study used the Korean Neonatal Network (KNN) dataset to develop ...
BMJ

Predicting the risks of kidney failure and death in adults with moderate to severe chronic kidney disease

The risk prediction model for kidney failure and death in people with chronic kidney disease (CKD) presented in the linked study is a super learner. A super learner is an algorithm that repeatedly ...
aibusiness

AI in the Advancement of Precision Nutrition

Lifestyle-mediated chronic conditions, such as heart disease, cancer, obesity and diabetes, account for 74% of annual deaths globally. These conditions are multifaceted in their origins, arising from ...