AIMC Topic: Humans

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Learning curves in laparoscopic and robot-assisted prostate surgery: a systematic search and review.

World journal of urology
PURPOSE: To perform a systematic search and review of the available literature on the learning curves (LCs) in laparoscopic and robot-assisted prostate surgery.

Chatbot breakthrough in the 2020s? An ethical reflection on the trend of automated consultations in health care.

Medicine, health care, and philosophy
Many experts have emphasised that chatbots are not sufficiently mature to be able to technically diagnose patient conditions or replace the judgements of health professionals. The COVID-19 pandemic, however, has significantly increased the utilisatio...

Deep learning model for diagnosing gastric mucosal lesions using endoscopic images: development, validation, and method comparison.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Endoscopic differential diagnoses of gastric mucosal lesions (benign gastric ulcer, early gastric cancer [EGC], and advanced gastric cancer) remain challenging. We aimed to develop and validate convolutional neural network-based ...

Diagnosing autism spectrum disorder in children using conventional MRI and apparent diffusion coefficient based deep learning algorithms.

European radiology
OBJECTIVE: To develop and validate deep learning (DL) methods for diagnosing autism spectrum disorder (ASD) based on conventional MRI (cMRI) and apparent diffusion coefficient (ADC) images.

MRI-guided attenuation correction in torso PET/MRI: Assessment of segmentation-, atlas-, and deep learning-based approaches in the presence of outliers.

Magnetic resonance in medicine
PURPOSE: We compare the performance of three commonly used MRI-guided attenuation correction approaches in torso PET/MRI, namely segmentation-, atlas-, and deep learning-based algorithms.

Detecting failure modes in image reconstructions with interval neural network uncertainty.

International journal of computer assisted radiology and surgery
PURPOSE: The quantitative detection of failure modes is important for making deep neural networks reliable and usable at scale. We consider three examples for common failure modes in image reconstruction and demonstrate the potential of uncertainty q...

Uterine Transplantation with Robot-assisted Uterus Retrieval from Living Donor: First Case in Brazil.

Journal of minimally invasive gynecology
OBJECTIVE: To present the first robot-assisted uterus retrieval from a living donor for uterine transplantation in Brazil.

Applying interpretable deep learning models to identify chronic cough patients using EHR data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Chronic cough (CC) affects approximately 10% of adults. Many disease states are associated with chronic cough, such as asthma, upper airway cough syndrome, bronchitis, and gastroesophageal reflux disease. The lack of an ICD ...