AIMC Topic: Female

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Predicting Pathological Complete Response Following Neoadjuvant Therapy in Patients With Breast Cancer: Development of Machine Learning-Based Prediction Models in a Retrospective Study.

JMIR cancer
BACKGROUND: Breast cancer is the most prevalent form of cancer worldwide, with 2.3 million new diagnoses in 2022. Recent advancements in treatment have led to a shift in the use of chemotherapy-targeted immunotherapy from a postoperative adjuvant to ...

AI-powered skin spectral imaging enables instant sepsis diagnosis and outcome prediction in critically ill patients.

Science advances
With sepsis remaining a leading cause of mortality, early identification of patients with sepsis and those at high risk of death is a challenge of high socioeconomic importance. Given the potential of hyperspectral imaging (HSI) to monitor microcircu...

Evaluating changes in hypoglossal nerve stimulator use over time and long-term adherence.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Evaluate patient phenotypes and longitudinal patterns of hypoglossal nerve stimulator (HGNS) use and identify predictors of long-term HGNS adherence.

An AI-assisted tool for automated growth monitoring in pediatric achondroplasia.

European journal of pediatrics
UNLABELLED: Growth assessment in achondroplasia requires disorder-specific growth charts incorporating sex- and age-specific values. Manual calculations are tedious and subject to error. We present an artificial intelligence (AI)-assisted tool that a...

AI-Based Facial Analysis vs Self-Report: A Pilot Study Using Insights From Pre-Procedural Psychological Tests.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Aesthetic procedures aligning with societal beauty standards are gaining popularity, often driven by unrealistic beauty ideals. However, these treatments frequently disappoint individuals with low self-esteem and distorted self-images. AI ...

Assessment and prediction models for the quantitative and qualitative reserve of the ovary using machine learning.

Journal of ovarian research
BACKGROUND: The age-related decline of fertility is caused by a reduction of the ovarian reserve, which is represented by the number and quality of oocytes in the ovaries. Anti-Müllerian hormone (AMH) is considered one of the most useful markers of t...

Establishment of an interpretable MRI radiomics-based machine learning model capable of predicting axillary lymph node metastasis in invasive breast cancer.

Scientific reports
This study sought to develop a radiomics model capable of predicting axillary lymph node metastasis (ALNM) in patients with invasive breast cancer (IBC) based on dual-sequence magnetic resonance imaging(MRI) of diffusion-weighted imaging (DWI) and dy...

Integrating bulk and single cell sequencing data to identify prognostic biomarkers and drug candidates in HBV associated hepatocellular carcinoma.

Scientific reports
Hepatitis B virus (HBV) infection is a major driver of hepatocellular carcinoma (HCC), yet the mechanisms by which HBV triggers HCC and how it interacts with the immune system remain largely undefined. In this study, 53 immune-related key genes invol...

Nancy histological index in ulcerative colitis: an interobserver study.

Journal of clinical pathology
The Nancy histological index (NHI) is a measure of disease activity within colorectal biopsies and a predictor of clinical outcome in ulcerative colitis (UC). We measured interobserver agreement (IOA) during NHI scoring of 20 colorectal biopsies in U...

Type of pre-existing chronic conditions and their associations with Merkel cell carcinoma (MCC) treatment: Prediction and interpretation using machine learning methods.

PloS one
OBJECTIVE: This study examined the prevalence of pre-existing chronic conditions and their association with the receipt of specific cancer-directed treatments among older adults with incident primary Merkel Cell Carcinoma (MCC) using novel predictive...