Background: Artificial Intelligence provides numerous applications in the healthcare sector. The main aim of this study is to evaluate the extent of the current application of artificial intelligence in thyroid diagnostics.
Methods: Our protocol was based on the Scoping Reviews extension of the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA-ScR). Information was gathered from PubMed, Cochrane, and EMBASE databases and Google Scholar. Eligible studies were published between 2017 and 2022.
Results: The search identified 133 records, after which 18 articles were included in the scoping review. All the publications were journal articles and discussed various ways that specialists in thyroid diagnostics and surgery have utilized artificial intelligence in their practice.
Conclusions: The development and incorporation of Artificial Intelligence applications in thyroid diagnostics and surgery has been moderate yet promising. However, applications are currently inconsistent and further research is needed to delineate the true benefit and limitations in this field.
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http://dx.doi.org/10.1016/j.amjsurg.2023.11.019 | DOI Listing |
Lymphology
January 2024
Medical Biophysics Department, Medical Research Institute, Alexandria University, Alexandria, Egypt.
Lymphadenopathy is associated with lymph node abnormal size or consistency due to many causes. We employed the deep convolutional neural network ResNet-34 to detect and classify CT images from patients with abdominal lymphadenopathy and healthy controls. We created a single database containing 1400 source CT images for patients with abdominal lymphadenopathy (n = 700) and healthy controls (n = 700).
View Article and Find Full Text PDFPharmaceut Med
January 2025
Pharmaceutical Medicine, Dover Heights, Sydney, NSW, Australia.
Pharmaceutical medicine professionals have to face many ethical problems during the entire life span of new medicines extending from animal studies to broad clinical practice. The primary aim of the general ethical principles governing research conducted in humans is to diminish the physical and psychological burdens of the participants in human drug studies but overlooks many additional social and ethical problems faced by medicine developers. These arise mainly at the interface connecting the profit-oriented pharmaceutical industry and the healthcare-centered medical profession cooperating in medicines development.
View Article and Find Full Text PDFPurpose: This brief report aims to summarize and discuss the methodologies of eXplainable Artificial Intelligence (XAI) and their potential applications in surgery.
Methods: We briefly introduce explainability methods, including global and individual explanatory features, methods for imaging data and time series, as well as similarity classification, and unraveled rules and laws.
Results: Given the increasing interest in artificial intelligence within the surgical field, we emphasize the critical importance of transparency and interpretability in the outputs of applied models.
Mol Biol Rep
January 2025
Division of Animal Genetics, ICAR-Indian Veterinary Research Institute (ICAR-IVRI), Izatnagar, Bareilly 243 122, Uttar Pradesh, India.
Background: Litter size in mice is an important fitness and economic feature that is controlled by several genes and influenced by non-genetic factors too. High positive selection pressure in each generation for Litter size at birth (LSB), resulted in the development of high and low prolific lines of inbred Swiss albino mice (SAM). Despite uniform management conditions, these lines showed variability in LSB across the generation.
View Article and Find Full Text PDFBrain Topogr
January 2025
Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India.
EEG involves recording electrical activity generated by the brain through electrodes placed on the scalp. Imagined speech classification has emerged as an essential area of research in brain-computer interfaces (BCIs). Despite significant advances, accurately classifying imagined speech signals remains challenging due to their complex and non-stationary nature.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!