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http://dx.doi.org/10.1590/1806-9282.20231362 | DOI Listing |
JMIR Med Inform
January 2025
Sungkyunkwan University, Seoul, Republic of Korea.
Background: Mental health chatbots have emerged as a promising tool for providing accessible and convenient support to individuals in need. Building on our previous research on digital interventions for loneliness and depression among Korean college students, this study addresses the limitations identified and explores more advanced artificial intelligence-driven solutions.
Objective: This study aimed to develop and evaluate the performance of HoMemeTown Dr.
Background: Large language models (LLMs) offer opportunities to enhance radiological applications, but their performance in handling complex tasks remains insufficiently investigated.
Purpose: To evaluate the performance of LLMs integrated with Contrast-enhanced Ultrasound Liver Imaging Reporting and Data System (CEUS LI-RADS) in diagnosing small (≤20mm) hepatocellular carcinoma (sHCC) in high-risk patients.
Materials And Methods: From November 2014 to December 2023, high-risk HCC patients with untreated small (≤20mm) focal liver lesions (sFLLs), were included in this retrospective study.
World J Mens Health
December 2024
Division of Urology, Department of Surgery, Far Eastern Memorial Hospital, New Taipei, Taiwan.
Purpose: Information retrieval (IR) and risk assessment (RA) from multi-modality imaging and pathology reports are critical to prostate cancer (PC) treatment. This study aims to evaluate the performance of four general-purpose large language model (LLMs) in IR and RA tasks.
Materials And Methods: We conducted a study using simulated text reports from computed tomography, magnetic resonance imaging, bone scans, and biopsy pathology on stage IV PC patients.
J Infect Public Health
December 2024
Department of Surgery, Hospital del Mar, Barcelona, Spain. Electronic address:
Background: Surveillance of surgical site infection (SSI) relies on manual methods that are time-consuming and prone to subjectivity. This study evaluates the diagnostic accuracy of ChatGPT for detecting SSI from electronic health records after colorectal surgery via comparison with the results of a nationwide surveillance programme.
Methods: This pilot, retrospective, multicentre analysis included 122 patients who underwent colorectal surgery.
J Nutr
December 2024
Department of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana, 010000, Kazakhstan. Electronic address:
Background: While large language models like ChatGPT-4 have demonstrated competency in English, their performance for minority groups speaking underrepresented languages, as well as their ability to adapt to specific socio-cultural nuances and regional cuisines, such as those in Central Asia (e.g., Kazakhstan), still requires further investigation.
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