AIMC Topic: Male

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Assessing operative variability in robot-assisted radical prostatectomy (RARP) through AI.

Journal of robotic surgery
Robotic-assisted radical prostatectomy (RARP) is the most commonly performed robotic procedure in urology. Using artificial intelligence (AI), surgical steps and practices can be assessed and validated through surgical video, and connected to patient...

Epidemiology and risk factors of Clonorchis sinensis infection in the mountainous areas of Longsheng County, Guangxi: insights from automated machine learning.

Parasitology research
Clonorchis sinensis (C. sinensis) is mainly prevalent in Northeast and South China, with Guangxi being the most severely affected region. This study aimed to evaluate the prevalence and identify the risk factors of C. sinensis infection in Longsheng ...

Machine Learning-Based Prediction of Delirium and Risk Factor Identification in Intensive Care Unit Patients With Burns: Retrospective Observational Study.

JMIR formative research
BACKGROUND: The incidence of delirium in patients with burns receiving treatment in the intensive care unit (ICU) is high, reaching up to 77%, and has been associated with increased mortality rates. Therefore, early identification of patients at high...

Use of natural language processing method to identify regional anesthesia from clinical notes.

Regional anesthesia and pain medicine
INTRODUCTION: Accurate data capture is integral for research and quality improvement efforts. Unfortunately, limited guidance for defining and documenting regional anesthesia has resulted in wide variation in documentation practices, even within indi...

Preoperative Maximum Standardized Uptake Value Emphasized in Explainable Machine Learning Model for Predicting the Risk of Recurrence in Resected Non-Small Cell Lung Cancer.

JCO clinical cancer informatics
PURPOSE: To comprehensively analyze the association between preoperative maximum standardized uptake value (SUV) on 18F-fluorodeoxyglucose positron emission tomography-computed tomography and postoperative recurrence in resected non-small cell lung c...

AI-determined similarity increases likability and trustworthiness of human voices.

PloS one
Modern artificial intelligence (AI) technology is capable of generating human sounding voices that could be used to deceive recipients in various contexts (e.g., deep fakes). Given the increasing accessibility of this technology and its potential soc...

Cell-free DNA in ex-vivo lung perfusate is associated with low-quality lungs and lung transplant outcome.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation
BACKGROUND: Cell-free DNA (cfDNA) in ex-vivo lung perfusion (EVLP) perfusate has been shown to potentially reflect lung injury; however, the relationship between cfDNA concentration with clinical EVLP lung outcomes has not been elucidated.

Morphological alterations of the thymus gland in individuals with schizophrenia.

Molecular psychiatry
Despite its critical function in the immune system and accumulating evidence of immunological abnormalities in schizophrenia, the thymus has long been overlooked. We aimed to investigate thymic morphological alterations and their corresponding hetero...

Development of Artificial Intelligence-Supported Automatic Three-Dimensional Surface Cephalometry.

Orthodontics & craniofacial research
OBJECTIVE: Surface-based three-dimensional (3D) cephalometry provides detailed clinical information for the analysis of craniofacial structures. This study aimed to develop an automated 3D surface cephalometry system using mesh fitting based on landm...

Predicting the complexity of minimally invasive liver resection for hepatocellular carcinoma using machine learning.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: Despite technical advancements, minimally invasive liver surgery (MILS) for hepatocellular carcinoma (HCC) remains challenging. Nonetheless, effective tools to assess MILS complexity are still lacking. Machine learning (ML) models could i...