AIMC Topic: Female

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Efficient Screening in Obstructive Sleep Apnea Using Sequential Machine Learning Models, Questionnaires, and Pulse Oximetry Signals: Mixed Methods Study.

Journal of medical Internet research
BACKGROUND: Obstructive sleep apnea (OSA) is a prevalent sleep disorder characterized by frequent pauses or shallow breathing during sleep. Polysomnography, the gold standard for OSA assessment, is time consuming and labor intensive, thus limiting di...

A Machine Learning-Based Prediction Model for Acute Kidney Injury in Patients With Community-Acquired Pneumonia: Multicenter Validation Study.

Journal of medical Internet research
BACKGROUND: Acute kidney injury (AKI) is common in patients with community-acquired pneumonia (CAP) and is associated with increased morbidity and mortality.

XGBoost-SHAP-based interpretable diagnostic framework for knee osteoarthritis: a population-based retrospective cohort study.

Arthritis research & therapy
OBJECTIVE: To use routine demographic and clinical data to develop an interpretable individual-level machine learning (ML) model to diagnose knee osteoarthritis (KOA) and to identify highly ranked features.

Evaluation of prediction errors in nine intraocular lens calculation formulas using an explainable machine learning model.

BMC ophthalmology
BACKGROUND: The purpose of the study was to evaluate the relationship between prediction errors (PEs) and ocular biometric variables in cataract surgery using nine intraocular lens (IOL) formulas with an explainable machine learning model.

Advanced analytical methods for multi-spectral transmission imaging optimization: enhancing breast tissue heterogeneity detection and tumor screening with hybrid image processing and deep learning.

Analytical methods : advancing methods and applications
Light sources exhibit significant absorption and scattering effects during the transmission through biological tissues, posing challenges in identifying heterogeneities in multi-spectral images. This paper introduces a fusion of techniques encompassi...

Artificial intelligence for better goals of care documentation.

BMJ supportive & palliative care
OBJECTIVES: Lower rates of goals of care (GOC) conversations have been observed in non-white hospitalised patients, which may contribute to racial disparities in end-of-life care. We aimed to assess how a targeted initiative to increase GOC documenta...

Artificial intelligence-based computer-aided diagnosis for breast cancer detection on digital mammography in Hong Kong.

Hong Kong medical journal = Xianggang yi xue za zhi
INTRODUCTION: Research concerning artificial intelligence in breast cancer detection has primarily focused on population screening. However, Hong Kong lacks a population-based screening programme. This study aimed to evaluate the potential of artific...

High density of TCF1+ stem-like tumor-infiltrating lymphocytes is associated with favorable disease-specific survival in NSCLC.

Frontiers in immunology
INTRODUCTION: Tumor-infiltrating lymphocytes are both prognostic and predictive biomarkers for immunotherapy response. However, less is known about the survival benefits oftheir subpopulations.

Machine-learning derived identification of prognostic signature to forecast head and neck squamous cell carcinoma prognosis and drug response.

Frontiers in immunology
INTRODUCTION: Head and neck squamous cell carcinoma (HNSCC), a highly heterogeneous malignancy is often associated with unfavorable prognosis. Due to its unique anatomical position and the absence of effective early inspection methods, surgical inter...

Cubosomes as Delivery System to Repositioning Nitrofurantoin in Breast Cancer Management.

Drug design, development and therapy
PURPOSE: Nitrofurantoin (NITRO), a long-standing antibiotic to treat urinary tract infections, is activated by Nitro reductases. This activation mechanism has led to its exploration for repositioning applications in controlling and treating breast ca...