A machine learning model can predict hepatocellular carcinoma (HCC) risk using routinely available data, according to a study ...

A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...

Using routine clinical data, the model gauges liver cancer risk better than existing tools, offering a potential way to identify high-risk patients missed by current screening criteria.

Sepsis is one of the most common and lethal syndromes encountered in intensive care units (ICUs), and acute respiratory ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient’s risk of hepatocellular carcinoma with high accuracy.

Mount Sinai researchers have created an analytic tool using machine learning that can predict cardiovascular disease risk in ...

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

Infinite dilution activity coefficient is a key thermodynamic parameter in solvent design for chemical processes. Although ...

A new study published in the journal Carbon Research introduces an advanced machine learning model capable of predicting how ...

Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study The use of real-world data ...

Stock Price Prediction, Deep Learning, LSTM, GRU, Attention Mechanism, Financial Time Series Share and Cite: Kirui, D. (2026) ...