AIMC Topic: Humans

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Edge roughness quantifies impact of physician variation on training and performance of deep learning auto-segmentation models for the esophagus.

Scientific reports
Manual segmentation of tumors and organs-at-risk (OAR) in 3D imaging for radiation-therapy planning is time-consuming and subject to variation between different observers. Artificial intelligence (AI) can assist with segmentation, but challenges exis...

Potential applications and implications of large language models in primary care.

Family medicine and community health
The recent release of highly advanced generative artificial intelligence (AI) chatbots, including ChatGPT and Bard, which are powered by large language models (LLMs), has attracted growing mainstream interest over its diverse applications in clinical...

Impact of AI-aided colonoscopy in clinical practice: a prospective randomised controlled trial.

BMJ open gastroenterology
OBJECTIVE: Colorectal cancer (CRC) has a significant role in cancer-related mortality. Colonoscopy, combined with adenoma removal, has proven effective in reducing CRC incidence. However, suboptimal colonoscopy quality often leads to missed polyps. T...

Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study.

Journal of medical Internet research
BACKGROUND: Sentiment analysis is a significant yet difficult task in natural language processing. The linguistic peculiarities of Cantonese, including its high similarity with Standard Chinese, its grammatical and lexical uniqueness, and its colloqu...

Machine Learning and Health Science Research: Tutorial.

Journal of medical Internet research
Machine learning (ML) has seen impressive growth in health science research due to its capacity for handling complex data to perform a range of tasks, including unsupervised learning, supervised learning, and reinforcement learning. To aid health sci...

Impact of visceral fat area on short-term outcomes in robotic surgery for mid and low rectal cancer.

Journal of robotic surgery
Rectal cancer is one of the most prevalent cancers that arise in the digestive tract. The purpose of this retrospective study was to investigate the impact of visceral fat area (VFA) on postoperative outcomes in mid and low rectal cancer patients und...

Machine learning models for predicting unscheduled return visits to an emergency department: a scoping review.

BMC emergency medicine
BACKGROUND: Unscheduled return visits (URVs) to emergency departments (EDs) are used to assess the quality of care in EDs. Machine learning (ML) models can incorporate a wide range of complex predictors to identify high-risk patients and reduce error...

Ultrafast diffusion tensor imaging based on deep learning and multi-slice information sharing.

Physics in medicine and biology
. Diffusion tensor imaging (DTI) is excellent for non-invasively quantifying tissue microstructure. Theoretically DTI can be achieved with six different diffusion weighted images and one reference image, but the tensor estimation accuracy is poor in ...

Optimizing robotic thyroid surgery: lessons learned from an retrospective analysis of 104 cases.

Frontiers in endocrinology
BACKGROUND: Robotic assistance in thyroidectomy is a developing field that promises enhanced surgical precision and improved patient outcomes. This study investigates the impact of the da Vinci Surgical System on operative efficiency, learning curve,...

Assessment of Color Reproducibility and Mitigation of Color Variation in Whole Slide Image Scanners for Toxicologic Pathology.

Toxicologic pathology
Digital pathology workflows in toxicologic pathology rely on whole slide images (WSIs) from histopathology slides. Inconsistent color reproduction by WSI scanners of different models and from different manufacturers can result in different color repr...