AIMC Topic: Retrospective Studies

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Inconsistency between Human Observation and Deep Learning Models: Assessing Validity of Postmortem Computed Tomography Diagnosis of Drowning.

Journal of imaging informatics in medicine
Drowning diagnosis is a complicated process in the autopsy, even with the assistance of autopsy imaging and the on-site information from where the body was found. Previous studies have developed well-performed deep learning (DL) models for drowning d...

Improved image quality in contrast-enhanced 3D-T1 weighted sequence by compressed sensing-based deep-learning reconstruction for the evaluation of head and neck.

Magnetic resonance imaging
PURPOSE: To assess the utility of deep learning (DL)-based image reconstruction with the combination of compressed sensing (CS) denoising cycle by comparing images reconstructed by conventional CS-based method without DL in fat-suppressed (Fs)-contra...

Application of deep learning for automated diagnosis and classification of hip dysplasia on plain radiographs.

BMC musculoskeletal disorders
BACKGROUND: Hip dysplasia is a condition where the acetabulum is too shallow to support the femoral head and is commonly considered a risk factor for hip osteoarthritis. The objective of this study was to develop a deep learning model to diagnose hip...

Automated detection of fatal cerebral haemorrhage in postmortem CT data.

International journal of legal medicine
During the last years, the detection of different causes of death based on postmortem imaging findings became more and more relevant. Especially postmortem computed tomography (PMCT) as a non-invasive, relatively cheap, and fast technique is progress...

Comparing the Quality of Domain-Specific Versus General Language Models for Artificial Intelligence-Generated Differential Diagnoses in PICU Patients.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVES: Generative language models (LMs) are being evaluated in a variety of tasks in healthcare, but pediatric critical care studies are scant. Our objective was to evaluate the utility of generative LMs in the pediatric critical care setting an...

Single-port vs multi-port robot-assisted partial nephrectomy: A single center propensity score-matched analysis.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
INTRODUCTION AND OBJECTIVES: The aim of the study is to compare key outcomes of Single-Port (SP) and Multi-Port (MP) robot-assisted partial nephrectomy (RAPN).

First clinical experiences of robotic gastrectomy for gastric cancer using the hinotori™ surgical robot system.

Surgical endoscopy
BACKGROUND: Although the da Vinci™ Surgical System is the most predominantly used surgical robot worldwide, other surgical robots are being developed. The Japanese surgical robot hinotori™ Surgical Robot System was launched and approved for clinical ...

Pediatric Robot-Assisted Laparoscopic Pyeloplasty: Where Are We Now?

Current urology reports
PURPOSE OF REVIEW: This review aims to provide an in-depth exploration of the recent advancements in robot-assisted laparoscopic pyeloplasty (RALP) and its evolving landscape in the context of infant pyeloplasty, complex genitourinary (GU) anatomy, r...

Application of Machine Learning Techniques to Assess Alpha-Fetoprotein at Diagnosis of Hepatocellular Carcinoma.

International journal of molecular sciences
Hepatocellular carcinoma (HCC) is the most common primary liver tumor and is associated with high mortality rates. Approximately 80% of cases occur in cirrhotic livers, posing a significant challenge for appropriate therapeutic management. Adequate s...