Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology
May 17, 2024
AIMS: There is limited data on the prevalence and risk factors of colonic adenoma from the Indian sub-continent. We aimed at developing a machine-learning model to optimize colonic adenoma detection in a prospective cohort.
OBJECTIVE: The aim of this study was to summarize the literature on the applications of machine learning (ML) and their performance in Emergency Medical Services (EMS).
The evaluation of morphologic features, such as inflammation, gastric atrophy, and intestinal metaplasia, is crucial for diagnosing gastritis. However, artificial intelligence analysis for nontumor diseases like gastritis is limited. Previous deep le...
BACKGROUND: In laparoscopic liver surgery, accurately predicting the displacement of key intrahepatic anatomical structures is crucial for informing the doctor's intraoperative decision-making. However, due to the constrained surgical perspective, on...
BACKGROUND AND OBJECTIVE: The accurate diagnosis of temporomandibular disorders continues to be a challenge, despite the existence of internationally agreed-upon diagnostic criteria. The purpose of this study is to review applications of deep learnin...
Cyberpsychology, behavior and social networking
May 17, 2024
Human moral reactions to artificial intelligence (AI) agents' behavior constitute an important aspect of modern-day human-AI relationships. Although previous studies have mainly focused on autonomy ethics, this study investigates how individuals judg...
Artificial intelligence (AI) platforms such as ChatGPT and Bard are increasingly utilized to answer patient health care questions. We present the first study to blindly evaluate AI-generated responses to common endourology patient questions against ...
Convolutional neural networks (CNNs) are gradually being recognized in the neuroimaging community as a powerful tool for image analysis. Despite their outstanding performances, some aspects of CNN functioning are still not fully understood by human o...
Deep learning-based image segmentation and detection models have largely improved the efficiency of analyzing retinal landmarks such as optic disc (OD), optic cup (OC), and fovea. However, factors including ophthalmic disease-related lesions and low ...
In the past 40 years, therapeutic antibody discovery and development have advanced considerably, with machine learning (ML) offering a promising way to speed up the process by reducing costs and the number of experiments required. Recent progress in ...
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