AIMC Topic: Retrospective Studies

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Effects of bisphosphonates after denosumab discontinuation and treatment effect heterogeneity using causal machine learning.

Scientific reports
Discontinuation of denosumab is associated with a rebound increase in osteoporotic fracture (OF) risk, and bisphosphonates (BPs) are commonly recommended as sequential therapy to mitigate this risk. However, their real-world effectiveness-and whether...

Deep learning-based 3D automatic segmentation of impacted canines in CBCT scans.

BMC oral health
BACKGROUND: Impacted canines are one of the most frequently encountered dental anomalies in maxillofacial practice. Accurate localization of these teeth is crucial for treatment planning, and Cone Beam Computed Tomography (CBCT) offers detailed 3D im...

Establishment of a postoperative delirium risk prediction model for elderly hip fracture patients based on machine learning algorithms.

BMC geriatrics
BACKGROUND: Although no definitive treatment exists, 30-40% of postoperative delirium cases are preventable through early risk identification and intervention. Therefore our aim was to develop and evaluate a postoperative delirium risk prediction mod...

Evaluating Multiple Input Strategies of Large Language Models for Gallbladder Polyps on Ultrasound: Comparative Study.

JMIR medical informatics
BACKGROUND: Gallbladder polyps have a high prevalence and are predominantly benign lesions, often detected via ultrasound. They impose diagnostic burdens on radiologists while generating substantial patient demand for report interpretation. Benign po...

Deep learning-based MRI model for predicting P53-mutated hepatocellular carcinoma.

BMC medical imaging
BACKGROUND: The P53-mutated Hepatocellular Carcinoma (HCC) is an aggressive variant associated with vascular endothelial growth factor (VEGF) overexpression and increased microvascular density. This study aimed to develop an MRI-based deep learning m...

A Machine Learning Model Based on Clinical Factors to Predict the Efficacy of First-Line Immunochemotherapy for Patients With Advanced Gastric Cancer: Retrospective Study.

JMIR medical informatics
BACKGROUND: The development of immunotherapy has provided new hope for patients with advanced gastric cancer (AGC). However, due to the high heterogeneity of the disease, the efficacy of first-line immunochemotherapy varies among patients. There is s...

Interpretable multimodal radiopathomics model predicting pathological complete response to neoadjuvant chemoimmunotherapy in esophageal squamous cell carcinoma.

Journal for immunotherapy of cancer
BACKGROUND: Accurate preoperative prediction of pathological complete response (pCR) following neoadjuvant chemoimmunotherapy (nCIT) could help individualize treatment for patients with esophageal squamous cell carcinoma (ESCC). This study aimed to d...

Development and validation of a screening model for early diagnosis of biliary atresia in neonates with cholestasis.

Pediatric surgery international
BACKGROUND: Biliary atresia (BA) is a progressive neonatal cholestatic liver disease that requires timely diagnosis and intervention. Differentiating BA from other causes of neonatal cholestasis remains a significant clinical challenge.

Connectomics in brain tumor surgery: large-scale clinical feasibility and hypothesis-generating tractometry findings.

Journal of neuro-oncology
BACKGROUND: Maximal tumor resection with neurological preservation is central to brain tumor surgery. This study evaluates the integration of an artificial intelligence-based connectomics platform for surgical planning, with exploratory tractometry a...

Application of risk prediction model to evaluate the effect of mechanical ventilation on postoperative pulmonary complications in thoracic surgery.

European journal of medical research
OBJECTIVE: This retrospective cohort study aimed to systematically evaluate the impact of different mechanical ventilation strategies on postoperative pulmonary complications (PPCs) in thoracic surgery and to establish a risk prediction model that fa...