Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

When integrated into healthcare, large language models (LLMs) have transformative and revolutionary effects, including significant potential for improving patient care and streamlining clinical processes. However, one specialty that particularly requires data on LLM use is gastroenterology and gastrointestinal surgery, a gap we sought to address in our research. Advanced artificial intelligence (AI) systems like LLMs have demonstrated the ability to mimic human communication, assist in diagnosis, provide patient education, and support medical research simultaneously. Despite these advantages, challenges such as biases, data privacy concerns, and lack of transparency in decision-making remain critical. The role of regulations in mitigating these risks is widely debated, with proponents advocating for structured oversight to enhance trust and patient safety, while others caution against potential barriers to innovation. Rather than replacing human expertise, AI should be integrated thoughtfully to complement clinical decision-making. Ensuring a balanced approach requires collaboration between medical professionals, AI developers, and policymakers to optimize its responsible implementation in healthcare.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12045793PMC
http://dx.doi.org/10.14740/gr2011DOI Listing

Publication Analysis

Top Keywords

large language
8
language models
8
gastroenterology gastrointestinal
8
gastrointestinal surgery
8
models gastroenterology
4
surgery frontier
4
patient
4
frontier patient
4
patient communication
4
communication education
4

Similar Publications

Patient-reported outcomes after lobectomy vs. segmentectomy for early-stage non-small cell lung cancer.

Surg Endosc

September 2025

Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.

Background: Surgical resection is the cornerstone for early-stage non-small cell lung cancer (NSCLC), with lobectomy historically standard. Evolving techniques have spurred debate comparing lobectomy and segmentectomy. This study analyzed early postoperative patient-reported symptoms and functional status in patients with early NSCLC undergoing either procedure.

View Article and Find Full Text PDF

Purpose: The study aims to compare the treatment recommendations generated by four leading large language models (LLMs) with those from 21 sarcoma centers' multidisciplinary tumor boards (MTBs) of the sarcoma ring trial in managing complex soft tissue sarcoma (STS) cases.

Methods: We simulated STS-MTBs using four LLMs-Llama 3.2-vison: 90b, Claude 3.

View Article and Find Full Text PDF

Background: Clinical communication is central to the delivery of effective, timely, and safe patient care. The use of text-based tools for clinician-to-clinician communication-commonly referred to as secure messaging-has increased exponentially over the past decade. The use of secure messaging has a potential impact on clinician work behaviors, workload, and cognitive burden.

View Article and Find Full Text PDF

Artificial Intelligence in allergy and immunology: recent developments, implementation challenges, and the road towards clinical impact.

J Allergy Clin Immunol

September 2025

University of Groningen, University Medical Center Groningen, Beatrix Children's Hospital, Department of Pediatric Pulmonology and Pediatric Allergology, Groningen, the Netherlands; University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC)

Artificial intelligence (AI) is increasingly recognized for its capacity to transform medicine. While publications applying AI in allergy and immunology have increased, clinical implementation substantially lags behind other specialties. By mid-2024, over 1,000 FDA-approved AI-enabled medical devices existed, but none specifically addressed allergy and immunology.

View Article and Find Full Text PDF

[Artificial Intelligence Methods - a Perspective for Cardiovascular Telemedicine?].

Dtsch Med Wochenschr

September 2025

Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charité Universitätsmedizin Berlin, Berlin, Deutschland.

Since 2022, an estimated 150000 to 200000 patients with heart failure (HF) in Germany have met the inclusion criteria for HF telemonitoring in accordance with the Federal Joint Committee's (G-BA) decision. Currently, only a few artificial intelligence (AI) applications are used in standard cardiovascular telemedicine care. However, AI applications could improve the predictive accuracy of existing telemedical sensor technology by recognising patterns across multiple data sources.

View Article and Find Full Text PDF