Menopause

Multi-omics predicts radiotherapy response in small cell lung cancer patients receiving whole brain irradiation.

OBJECTIVE: Dosiomics and radiomics elaborate the low-and high-order features extracted from images to predict clinical outcomes. Whole-brain radiotherapy (WBRT) has been widely used in patients with diffuse brain metastases of small cell lung cancer (SCLC). The objective of this study is to ascertain the predictors of treatment response in patients with SCLC treated with WBRT. Furthermore, the stu...

Interval cancer, sensitivity, and specificity comparing AI-supported mammography screening with standard double reading without AI in the MASAI study: a randomised, controlled, non-inferiority, single-blinded, population-based, screening-accuracy trial.

BACKGROUND: Evidence indicates that artificial intelligence (AI) can improve mammography screening by increasing cancer detection and reducing screen reading workload, but its effect on interval cancers (primary breast cancers diagnosed between two screening rounds or within 2 years after the last scheduled screening that were not detected at screening) is unknown. We aimed to compare the interval...

Predicting nonresponse to sexual identity question in youth risk behavior surveillance: A machine learning analysis of complex survey data.

PURPOSE: To compare seven machine learning (ML) models developed to predict non-response to the sexual identity question in the 2023 Youth Risk Behavi...

Circulating tumor DNA dynamics predict pathological response and guide therapy personalization in the neoadjuvant setting.

Neoadjuvant therapy is a cornerstone of modern oncology, yet its efficacy is traditionally assessed only after treatment completion, creating a "black...

Osteoporosis prediction using lumbar CT Hounsfield units: comparative performance and clinical implications of seven machine learning models.

PURPOSE: This study aimed to evaluate the utility of L1-L4 average Hounsfield Unit (HU) values from lumbar spine computed tomography (CT) in predictin...

Lipid monitoring using non-invasive measurement technologies and machine learning: a systematic review.

BACKGROUND: Cardiovascular diseases (CVD) are the leading cause of death among women, with risk increasing after menopause. Lipid levels are key bioma...

Padé Neurons for Efficient Neural Models.

Neural networks commonly employ the McCulloch-Pitts neuron model, which is a linear model followed by a point-wise non-linear activation. Various rese...

Health trajectories of patients with amyotrophic lateral sclerosis before and after initiation of non-invasive ventilation: a French nationwide database analysis.

BACKGROUND: Management of amyotrophic lateral sclerosis (ALS) is complicated by heterogeneous presentation and unpredictable disease course. This stud...

Hierarchy and hope: Exploring AI's role in medicine through a thematic analysis of online discourse.

The healthcare community remains divided on the benefits of artificial intelligence (AI) in medicine. In this qualitative study, we sought to better u...

Childhood dyslexia risk elevated by heavy metal mixtures from e-waste: A machine learning-driven mixture modeling study.

Environmental heavy metal mixtures from informal e-waste recycling are potential neurotoxicants, but their link to developmental dyslexia remains uncl...

Novel mechanisms of atrazine endocrine disruption: an integrated approach reveals progesterone and glucocorticoid receptor targeting.

Automated Abdominal Aortic Calcification Scores and Atherosclerotic Cardiovascular Disease in the UK Biobank Imaging Study.

BACKGROUND: Abdominal aortic calcification (AAC) is a subclinical measure of atherosclerotic cardiovascular disease (ASCVD). AAC can be captured on la...

Integrated omics and machine learning uncover the molecular basis of environmental toxicant 6PPD-Qinduced non-obstructive azoospermia.

BACKGROUND: N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine-quinone (6PPD-Q), a transformation product of tire rubber antioxidants, has been increa...

Organ preservation in rectal cancer: an endoscopist's perspective on current evidence and future directions.

Rectal cancer management has increasingly shifted toward organ-preserving strategies that aim to maintain oncologic control while preserving bowel, ur...

Prospective Diagnostic Accuracy and Technical Feasibility of Artificial Intelligence-Assisted Rib Fracture Detection on Chest Radiographs: Observational Study.

BACKGROUND: Rib fractures are present in 10%-15% of thoracic trauma cases but are often missed on chest radiographs, delaying diagnosis and treatment....

Analysis of differential photoplethysmography signal patterns in apnea and hypopnea.

OBJECTIVE: Photoplethysmography, a non-invasive optical technique that measures changes in blood volume in the microvascular bed of tissue, offers a p...

Hierarchical image pyramid transformer framework for automated breast cancer molecular subtyping using tissue microarrays.

The heterogeneity of breast cancer at molecular and histological levels poses significant challenges for precise diagnosis and treatment. Current mole...

Microbiome-Based Modeling of CAR-T Therapy Response in Lymphoma: Insights From Shotgun Metagenomics Sequencing.

The interplay between the commensal microbiota and the mammalian immune system may influence the outcomes of T cell-driven cancer immunotherapies. How...

[Sphincter-preserving surgery for rectal cancer--From limits to perfection].

Sphincter-preserving therapy for low rectal cancer has always been a difficult and hot topic in colorectal cancer. Advanced understanding of the biolo...

Deciphering Multitarget Mechanisms of Phytochemical Flavonoids From Traditional Chinese Medicine: Emerging Insights Into Osteoporosis Therapeutics.

Osteoporosis is a common metabolic bone disorder characterized by reduced bone mass and compromised skeletal microstructure, increasing fracture risk....