AIMC Topic: Machine Learning

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Reporting of demographic data and representativeness in machine learning models using electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The development of machine learning (ML) algorithms to address a variety of issues faced in clinical practice has increased rapidly. However, questions have arisen regarding biases in their development that can affect their applicability i...

Machine-learning prediction of unplanned 30-day rehospitalization using the French hospital medico-administrative database.

Medicine
Predicting unplanned rehospitalizations has traditionally employed logistic regression models. Machine learning (ML) methods have been introduced in health service research and may improve the prediction of health outcomes. The objective of this work...

A machine learning based intramolecular potential for a flexible organic molecule.

Faraday discussions
Quantum mechanical predictive modelling in chemistry and biology is often hindered by the long time scales and large system sizes required of the computational model. Here, we employ the kernel regression machine learning technique to construct an an...

Machine learning-based approaches for disease gene prediction.

Briefings in functional genomics
Disease gene prediction is an essential issue in biomedical research. In the early days, annotation-based approaches were proposed for this problem. With the development of high-throughput technologies, interaction data between genes/proteins have gr...

Regulatory genes identification within functional genomics experiments for tissue classification into binary classes via machine learning techniques.

JPMA. The Journal of the Pakistan Medical Association
OBJECTIVE: The aim of this study is to filter out the most informative genes that mainly regulate the target tissue class, increase classification accuracy, reduce the curse of dimensionality, and discard redundant and irrelevant genes.

New perspectives in the prediction of postoperative complications for high-risk ulcerative colitis patients: machine learning preliminary approach.

European review for medical and pharmacological sciences
OBJECTIVE: Patients with acute severe and medical refractory ulcerative colitis have a high risk of postoperative complications after total abdominal colectomy (TAC). The objective of this retrospective study is to use machine learning to analyze and...

[Artificial intelligence systems and precision medicine: hopes and realities.].

Recenti progressi in medicina
Precision medicine (MP), using machine learning (ML) techniques of artificial intelligence (AI), analyzes the so-called "big data" to improve diagnostic skills and predictive response to therapy, in order to tailor the treatment on individual charact...