Journal of computer-aided molecular design
Jan 12, 2026
The integration of artificial intelligence (AI) with molecular modeling offers new opportunities to accelerate therapeutic discovery. In this study, we developed an AI-driven generative pipeline combining deep reinforcement learning (DRL), generative...
Endometrial cancer (EC) molecular subtyping is critical for prognosis and treatment but remains hindered by reliance on invasive tissue biopsies and time-consuming genomic sequencing. Here, we present a minimally invasive approach integrating MALDI-T...
BACKGROUND: Preoperative endometrial cancer (EC) diagnosis often depends on radiologists' expertise, which introduces subjectivity. Recent studies have explored radiomics-based machine learning (ML) models for detecting myometrial invasion (MI), but ...
Endometrial cancer (EC) is the most common gynecologic malignancy, with a steadily increasing incidence worldwide. Abnormal vaginal bleeding, a hallmark symptom, enables early diagnosis, which is critical for improving clinical outcomes. Pelvic magne...
Endometrial carcinoma (EC) has demonstrated a concerning epidemiological trajectory. Current evaluation systems for EC are limited to postoperative analysis, necessitating the development of a preoperative risk stratification model. Researchers aimed...
OBJECTIVES: This study aimed to develop and validate a CT radiomics-based explainable machine learning model for precise diagnosing of malignancy and benignity specifically in endometrial cancer (EC) patients.
AlphaFold, a deep learning-based platform widely used to predict protein and peptide structures, was employed in this study to model the self-assembling peptide RFC, which demonstrated a stable α-helical structure with high confidence. This structura...
Non-invasive preoperative assessment of HER2 status is critical for identifying candidates for targeted therapy and personalizing treatment strategies in endometrial cancer (EC). This study aims to assess the preoperative value of multiparametric mag...
BACKGROUND: Current ultrasound-based screening for endometrial cancer (EC) primarily relies on endometrial thickness (ET) and morphological evaluation, which suffer from low specificity and high interobserver variability. This study aimed to develop ...
Osteoarthritis (OA) has been implicated in the development and progression of early-stage endometrial cancer (EC), suggesting shared pathogenic factors between the two diseases. This study aimed to investigate the causal relationship between OA and E...
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