Objective: Information retrieval (IR, also known as search) systems are ubiquitous in modern times. How does the emergence of generative artificial intelligence (AI), based on large language models (LLMs), fit into the IR process?
Process: This perspective explores the use of generative AI in the context of the motivations, considerations, and outcomes of the IR process with a focus on the academic use of such systems.
Conclusions: There are many information needs, from simple to complex, that motivate use of IR. Users of such systems, particularly academics, have concerns for authoritativeness, timeliness, and contextualization of search. While LLMs may provide functionality that aids the IR process, the continued need for search systems, and research into their improvement, remains essential.
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http://dx.doi.org/10.1093/jamia/ocae014 | DOI Listing |
Cureus
December 2024
Radiology, Vancouver General Hospital, Vancouver, CAN.
Background: Although the number of women entering dermatology residency programs is increasing, they still encounter numerous challenges and disparities, including limited career opportunities and difficulties in balancing family planning with their professional lives. Parental leave policies have been recognized for their positive impact on maternal, fetal, and familial well-being, career satisfaction, and gender equality. However, negative perceptions and a lack of awareness surrounding these policies may discourage female residents from taking parental leave during training.
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December 2024
Internal Medicine, Belgaum Institute of Medical Science, Belgaum, IND.
Several studies explored the application of artificial intelligence (AI) in magnetic resonance imaging (MRI)-based rectal cancer (RC) staging, but a comprehensive evaluation remains lacking. This systematic review aims to review the performance of AI models in MRI-based RC staging. PubMed and Embase were searched from the inception of the database till October 2024 without any language and year restrictions.
View Article and Find Full Text PDFInt J Endocrinol Metab
July 2024
Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Context: Metabolic disorders are a growing global concern, especially in developed countries, due to their increasing prevalence. Serum lipid profiles, including triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL), and low-density lipoprotein (LDL), are commonly used clinical biomarkers for monitoring the progression of these metabolic abnormalities. In recent decades, hydrogen-rich water (HRW) has gained attention as a safe and effective treatment, with regulatory effects on lipid peroxidation and inflammatory responses in clinical trials.
View Article and Find Full Text PDFFront Oncol
January 2025
School of Engineering, Newcastle University, Newcastle Upon Tyne, United Kingdom.
Background: Non-muscle-invasive Bladder Cancer (NMIBC) is notorious for its high recurrence rate of 70-80%, imposing a significant human burden and making it one of the costliest cancers to manage. Current prediction tools for NMIBC recurrence rely on scoring systems that often overestimate risk and lack accuracy. Machine learning (ML) and artificial intelligence (AI) are transforming oncological urology by leveraging molecular and clinical data to enhance predictive precision.
View Article and Find Full Text PDFClin Neuropsychiatry
December 2024
Obsessive, Compulsive, and Anxiety Spectrum Research Program. Institute of Psychiatry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
Objective: Obsessive-compulsive and related disorders (OCRDs) and disorders due to addictive behavior (DABs) are prevalent conditions that share common neurobiological and behavioral characteristics. This scoping review aims to identify and map the range of subjective assessment tools (e.g.
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