AIMC Topic: Machine Learning

Clear Filters Showing 5121 to 5130 of 34417 articles

Radiomics integration based on intratumoral and peritumoral computed tomography improves the diagnostic efficiency of invasiveness in patients with pure ground-glass nodules: a machine learning, cross-sectional, bicentric study.

Journal of cardiothoracic surgery
BACKGROUND: Radiomics has shown promise in the diagnosis and prognosis of lung cancer. Here, we investigated the performance of computed tomography-based radiomic features, extracted from gross tumor volume (GTV), peritumoral volume (PTV), and GTV + ...

A novel method for screening malignant hematological diseases by constructing an optimal machine learning model based on blood cell parameters.

BMC medical informatics and decision making
BACKGROUND: Screening of malignant hematological diseases is of great importance for their diagnosis and subsequent treatment. This study constructed an optimal screening model for malignant hematological diseases based on routine blood cell paramete...

Machine learning approaches for predicting fetal macrosomia at different stages of pregnancy: a retrospective study in China.

BMC pregnancy and childbirth
BACKGROUND: Macrosomia presents significant risks to both maternal and neonatal health, however, accurate antenatal prediction remains a major challenge. This study aimed to develop machine learning approaches to enhance the prediction of fetal macro...

Identification of critical biomarkers and immune infiltration in preeclampsia through bioinformatics and machine learning methods.

BMC pregnancy and childbirth
BACKGROUND: Preeclampsia (PE) is a multisystem progressive disease that occurs during pregnancy. Previous studies have shown that the immune system is involved in the placental trophoblast function and the pathological process of uterine vascular rem...

A hybrid machine learning framework for functional annotation of mitochondrial glutathione transport and metabolism proteins in cancers.

BMC bioinformatics
BACKGROUND: Alterations of metabolism, including changes in mitochondrial metabolism as well as glutathione (GSH) metabolism are a well appreciated hallmark of many cancers. Mitochondrial GSH (mGSH) transport is a poorly characterized aspect of GSH m...

A promising AI based super resolution image reconstruction technique for early diagnosis of skin cancer.

Scientific reports
Skin cancer can be prevalent in people of any age group who are exposed to ultraviolet (UV) radiation. Among all other types, melanoma is a notable severe kind of skin cancer, which can be fatal. Melanoma is a malignant skin cancer arising from melan...

Machine learning with label-free Raman microscopy to investigate ferroptosis in comparison with apoptosis and necroptosis.

Communications biology
Human and animal health rely on balancing cell division and cell death to maintain normal homeostasis. This process is accomplished by regulated cell death (RCD), whose imbalance can lead to disease. Currently, the most frequently used method for ana...

Predictive modeling of methadone poisoning outcomes in children ≤ 5 years: utilizing machine learning and the National Poison Data System for improved clinical decision-making.

European journal of pediatrics
UNLABELLED: The escalating therapeutic use of methadone has coincided with an increase in accidental ingestions, particularly among children ≤ 5 years. This study utilized machine learning (ML) methodologies on data from the National Poison Data Syst...

BrainForest: Neuromorphic Multiplier-Less Bit-Serial Weight-Memory-Optimized 1024-Tree Brain-State Classification Processor.

IEEE transactions on biomedical circuits and systems
Personalized brain implants have the potential to revolutionize the treatment of neurological disorders and augment cognition. Medical implants that deliver therapeutic stimulation in response to detected seizures have already been deployed for the t...

SHASI-ML: a machine learning-based approach for immunogenicity prediction in vaccine development.

Frontiers in cellular and infection microbiology
INTRODUCTION: Accurate prediction of immunogenic proteins is crucial for vaccine development and understanding host-pathogen interactions in bacterial diseases, particularly for Salmonella infections which remain a significant global health challenge...