AIMC Topic: Machine Learning

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Comparison of the Capacity of Several Machine Learning Tools to Assist Immunofluorescence-Based Detection of Anti-Neutrophil Cytoplasmic Antibodies.

International journal of molecular sciences
The success of artificial intelligence and machine learning is an incentive to develop new algorithms to increase the rapidity and reliability of medical diagnosis. Here we compared different strategies aimed at processing microscope images used to d...

Evaluation metrics and statistical tests for machine learning.

Scientific reports
Research on different machine learning (ML) has become incredibly popular during the past few decades. However, for some researchers not familiar with statistics, it might be difficult to understand how to evaluate the performance of ML models and co...

The integration of artificial intelligence in robotic surgery: A narrative review.

Surgery
BACKGROUND: The rise of high-definition imaging and robotic surgery has independently been associated with improved postoperative outcomes. However, steep learning curves and finite human cognitive ability limit the facility in imaging interpretation...

A review of ADHD detection studies with machine learning methods using rsfMRI data.

NMR in biomedicine
Attention deficit hyperactivity disorder (ADHD) is a common mental health condition that significantly affects school-age children, causing difficulties with learning and daily functioning. Early identification is crucial, and reliable and objective ...

Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty.

Clinical orthopaedics and related research
BACKGROUND: Estimating the risk of revision after arthroplasty could inform patient and surgeon decision-making. However, there is a lack of well-performing prediction models assisting in this task, which may be due to current conventional modeling a...

Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery: a systematic review and meta-analysis.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Machine learning (ML) approaches have become increasingly popular in predicting surgical outcomes. However, it is unknown whether they are superior to traditional statistical methods such as logistic regression (LR). This study aimed to p...

Artificial intelligence in the diagnosis and treatment of acute appendicitis: a narrative review.

Updates in surgery
Artificial intelligence is transforming healthcare. Artificial intelligence can improve patient care by analyzing large amounts of data to help make more informed decisions regarding treatments and enhance medical research through analyzing and inter...

Schistocyte detection in artificial intelligence age.

International journal of laboratory hematology
Schistocytes are fragmented red blood cells produced as a result of mechanical damage to erythrocytes, usually due to microangiopathic thrombotic diseases or mechanical factors. The early laboratory detection of schistocytes has a critical impact on ...

Do machine learning methods lead to similar individualized treatment rules? A comparison study on real data.

Statistics in medicine
Identifying patients who benefit from a treatment is a key aspect of personalized medicine, which allows the development of individualized treatment rules (ITRs). Many machine learning methods have been proposed to create such rules. However, to what...

Reliable prediction of difficult airway for tracheal intubation from patient preoperative photographs by machine learning methods.

Computer methods and programs in biomedicine
BACKGROUND: Estimating the risk of a difficult tracheal intubation should help clinicians in better anaesthesia planning, to maximize patient safety. Routine bedside screenings suffer from low sensitivity.