AIMC Topic: Machine Learning

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Impact of heart failure on reoperation in adult congenital heart disease: An innovative machine learning model.

The Journal of thoracic and cardiovascular surgery
OBJECTIVES: The study objectives were to evaluate the association between preoperative heart failure and reoperative cardiac surgical outcomes in adult congenital heart disease and to develop a risk model for postoperative morbidity/mortality.

Distinct chemical environments in biomolecular condensates.

Nature chemical biology
Diverse mechanisms have been described for selective enrichment of biomolecules in membrane-bound organelles, but less is known about mechanisms by which molecules are selectively incorporated into biomolecular assemblies such as condensates that lac...

Machine learning in clinical practice: Evaluation of an artificial intelligence tool after implementation.

Emergency medicine Australasia : EMA
OBJECTIVE: Artificial intelligence (AI) has gradually found its way into healthcare, and its future integration into clinical practice is inevitable. In the present study, we evaluate the accuracy of a novel AI algorithm designed to predict admission...

Machine Learning for the Prediction of Survival Post-Allogeneic Hematopoietic Cell Transplantation: A Single-Center Experience.

Acta haematologica
INTRODUCTION: Prediction of outcomes following allogeneic hematopoietic cell transplantation (HCT) remains a major challenge. Machine learning (ML) is a computational procedure that may facilitate the generation of HCT prediction models. We sought to...

Disclosing the locale of transmembrane proteins within cellular alcove by machine learning approach: systematic review and meta analysis.

Journal of biomolecular structure & dynamics
Protein subcellular localization is a promising research question in Proteomics and associated fields, including Biological Sciences, Biomedical Engineering, Computational Biology, Bioinformatics, Proteomics, Artificial Intelligence, and Biophysics. ...

Application of Machine Learning Algorithms to Metadynamics for the Elucidation of the Binding Modes and Free Energy Landscape of Drug/Target Interactions: a Case Study.

Chemistry (Weinheim an der Bergstrasse, Germany)
In the context of drug discovery, computational methods were able to accelerate the challenging process of designing and optimizing a new drug candidate. Amongst the possible atomistic simulation approaches, metadynamics (metaD) has proven very power...

Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
OBJECTIVE: Mammogram-based automatic breast cancer detection has a primary role in accurate cancer diagnosis and treatment planning to save valuable lives. Mammography is one basic yet efficient test for screening breast cancer. Very few comprehensiv...

Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia.

Journal of neural engineering
(SCZ) is a severe mental disorder associated with persistent or recurrent psychosis, hallucinations, delusions, and thought disorders that affect approximately 26 million people worldwide, according to the World Health Organization. Several studies e...

Revolutionizing drug formulation development: The increasing impact of machine learning.

Advanced drug delivery reviews
Over the past few years, the adoption of machine learning (ML) techniques has rapidly expanded across many fields of research including formulation science. At the same time, the use of lipid nanoparticles to enable the successful delivery of mRNA va...

Applications for Deep Learning in Epilepsy Genetic Research.

International journal of molecular sciences
Epilepsy is a group of brain disorders characterised by an enduring predisposition to generate unprovoked seizures. Fuelled by advances in sequencing technologies and computational approaches, more than 900 genes have now been implicated in epilepsy....