A machine learning model using routine lab data at 3 months postdiagnosis accurately predicted mortality or liver transplant risk in autoimmune hepatitis.

Lunai Bioworks Announces Publication of Second-Generation Allogeneic Dendritic Cell Therapy Platform in the journal "Vaccines ...

Machine learning models using initial neuropsychological and neuropsychiatric clinical data accurately distinguished AD from bvFTD.

An analysis of 5 machine-learning algorithms identified predictors for moderate-to-severe cancer-related fatigue in patients with CRC undergoing chemotherapy.

Their study is centred around answering three research questions: Do ANNs perform better than the traditional multiple regression models in the prediction of lighting parameters and energy demand of ...

A machine learning model using basic clinical data can predict PH risk, identifying key predictors like low hemoglobin and elevated NT-proBNP. Researchers have developed a machine learning model that ...

Rather than study how to use AI, students in this machine learning class work with the math that makes the AI work.

Older Canadian adults whose physicians prescribe first-generation antihistamines in the hospital are more likely to ...

Wang, Z. (2025) Research on Prediction of Air Quality CO Concentration Based on Python Machine Learning. Advances in Internet ...

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...

Abstract: Machine learning models for continuous outcomes often yield systematically biased predictions, particularly for values that largely deviate from the mean. Specifically, predictions for large ...

ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...