Latest AI and machine learning research in peptic ulcer disease for healthcare professionals.
Protein modeling has largely centered on sequence representations, leaving the geometry and physicochemical context of molecular surfaces underused. We introduce PSMa (Protein Surface Masked autoencoder), a self-supervised framework that operates directly on molecular-surface point clouds with geometric and physicochemical attributes, reconstructing masked surface patches to learn transferable rep...
BACKGROUD: Â No universally accepted model exists for predicting bleeding risk in patients receiving low-molecular-weight heparin or fondaparinux. OBJECTIVE: Â This study leveraged seven machine learning algorithms to build a short-term bleeding risk prediction platform for this population. METHODS: Â This retrospective real-world observational study included hospitalized patients who received low-mo...
AIM: To develop and validate a deep learning-based AI system for the dynamic, real-time differentiation of benign and malignant gastric ulcers during ...
Subepithelial lesions (SELs) of the gastrointestinal tract encompass a heterogeneous spectrum of histology, ranging from benign to malignant. Their de...
BACKGROUND: Postoperative gastrointestinal (GI) bleeding is a serious complication after hip fracture surgery in older adults, yet perioperative risk ...
OBJECTIVE: Surgical procedures involving varying tissue depths present challenges to surgeons regarding accessibility and precision, restricting instr...
OBJECTIVES: Artificial intelligence (AI)-assisted endoscopy has been developed for the early detection of upper gastrointestinal cancer; however, its ...
Across surgical specialties, minimally invasive (laparoscopic) surgery has become a standard technique, as it is associated with less trauma, reduced ...
The key pathophysiological feature of obstructive sleep apnea（OSA） is dynamic collapse of the upper airway during sleep. Polysomnography（PSG） and awak...
BACKGROUND: Perioperative anticoagulant management is critical because of the competing risks of ischemia and bleeding. Large language models (LLMs) a...
BACKGROUND: Participatory approaches (including co-research, co-design, Patient and Public Involvement [PPI], and Participatory Action Research [PAR])...
In this study, we present an innovative approach in medicine, leveraging the potential of artificial intelligence (AI) for the diagnosis of tympanic m...
Ageing-related diseases (ARDs) display diverse phenotypes yet share an age-dependent rise in incidence, suggesting mechanistic links with ageing proce...
Polysomnography is the standard tool for assessing obstructive sleep apnea (OSA) severity; however, it does not provide information regarding the anat...
Artificial intelligence (AI) is increasingly used in gastrointestinal endoscopy for polyp detection and classification. However, most AI models are tr...
The long, tortuous, and tissue-homogeneous structure of the small bowel makes image-based three-dimensional (3D) modeling studies technically complex....
Artificial intelligence (AI) has the potential of reshaping GI oncology by enabling more nuanced interpretation of complex clinical, imaging, and mole...
INTRODUCTION: Typhoid intestinal perforation (TIP) remains a significant cause of pediatric morbidity in resource-limited settings, with prolonged hos...
OBJECTIVE: This feasibility study aimed to assess the potential of freely available large language models (LLMs) to support clinical decision-making i...