The latest version ChatGPT powered by GPT-4o: what will it bring to the medical field?

International Journal of Surgery, Journal Year: 2024, Volume and Issue: 110(9), P. 6018 - 6019

Published: June 10, 2024

Zhang, Nan MD; Sun, Zaijie Xie, Yuchen BS; Wu, Haiyang Li, Cheng PhD Author Information

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Artificial intelligence for image recognition in diagnosing oral and oropharyngeal cancer and leukoplakia

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 29, 2025

Visual diagnosis is one of the key features squamous cell carcinoma oral cavity (OSCC) and oropharynx (OPSCC), both subsets head neck (HNSCC) with a heterogeneous clinical appearance. Advancements in artificial intelligence led to Image recognition being introduced recently into large language models (LLMs) such as ChatGPT 4.0. This exploratory study, for first time, evaluated application image by diagnose leukoplakia based on images, images without any lesion control group. A total 45 were analyzed, comprising 15 cases each SCC, leukoplakia, non-lesion images. 4.0 was tasked providing most likely these scenario one. In two history provided, whereas three only given. The results accuracy LLM rated independent reviewers overall performance using modified Artificial Intelligence Performance Index (AIPI. this demonstrated ability correctly identify alone, while SCC insufficient, but improved including prompt. Providing resulted misclassification some cases. Oral lesions more be diagnosed correctly. study lesions, convincing detecting when added, Leukoplakia detected solely recognition. therefore currently insufficient reliable OPSCC OSCC diagnosis, further technological advancements may pave way use setting.

Language: Английский

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Adaptive Treatment of Metastatic Prostate Cancer Using Generative Artificial Intelligence

Clinical Medicine Insights Oncology, Journal Year: 2025, Volume and Issue: 19

Published: Jan. 1, 2025

Despite the expanding therapeutic options available to cancer patients, resistance, disease recurrence, and metastasis persist as hallmark challenges in treatment of cancer. The rise prominence generative artificial intelligence (GenAI) many realms human activities is compelling consideration its capabilities a potential lever advance development effective treatments. This article presents hypothetical case study on application pre-trained transformers (GPTs) metastatic prostate (mPC). explores design GPT-supported adaptive intermittent therapy for mPC. Testosterone prostate-specific antigen (PSA) are assumed be repeatedly monitored while may involve combination androgen deprivation (ADT), receptor-signalling inhibitors (ARSI), chemotherapy, radiotherapy. analysis covers various questions relevant configuration, training, inferencing GPTs mPC with particular attention risk mitigation regarding hallucination problem implications clinical integration GenAI technologies. provides elements an actionable pathway realization GenAI-assisted As such, expected help facilitate trials GenAI-supported

Language: Английский

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The Diagnostic Ability of GPT-3.5 and GPT-4.0 in Surgery: Comparative Analysis

Journal of Medical Internet Research, Journal Year: 2024, Volume and Issue: 26, P. e54985 - e54985

Published: Sept. 10, 2024

ChatGPT (OpenAI) has shown great potential in clinical diagnosis and could become an excellent auxiliary tool practice. This study investigates evaluates diagnostic capabilities by comparing the performance of GPT-3.5 GPT-4.0 across model iterations.

Language: Английский

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Utilizing Large Language Models for Educating Patients About Polycystic Ovary Syndrome in China: A Two-Phase Study (Preprint)

Published: Feb. 17, 2025

Polycystic ovary syndrome (PCOS) is a prevalent condition requiring effective patient education, particularly in China. Large language models (LLMs) present promising avenue for this. This two-phase study evaluates six LLMs educating Chinese patients about PCOS. It assesses their capabilities answering questions, interpreting ultrasound images, and providing instructions within real-world clinical setting systematically evaluated gigantic models—Gemini 2.0 Pro, OpenAI o1, ChatGPT-4o, ChatGPT-4, ERINE 4.0, GLM-4—for use gynecological medicine. assessed performance several areas: questions from the Gynecology Qualification Examination, understanding coping with polycystic cases, writing instructions, helping to solve problems. A two-step evaluation method was used. Primarily, they tested frameworks on 136 exam 36 images. They then compared results those of medical students residents. Six gynecologists framework's responses 23 PCOS-related using Likert scale, readability tool used review content objectively. In following process, 40 PCOS two central systems, Gemini Pro o1. them terms satisfaction, text readability, professional evaluation. During initial phase testing, o1 demonstrated impressive accuracy specialist achieving rates 93.63% 92.40%, respectively. Additionally, image diagnostic tasks noteworthy, an 69.44% reaching 53.70%. Regarding response significantly outperformed other accuracy, completeness, practicality, safety. However, its were notably more complex (average score 13.98, p = 0.003). The second-phase revealed that excelled (patient rating 3.45, < 0.01; physician 3.35, 0.03), surpassing 2.65, 2.90). slightly lagged behind completeness (3.05 vs. 3.50, 0.04). reveals large have considerable potential address issues faced by PCOS, which are capable accurate comprehensive responses. Nevertheless, it still needs be strengthened so can balance clarity comprehensiveness. addition, big besides analyzing especially ability handle regulation categories, improved meet practice. None

Language: Английский

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Can ChatGPT be used as a scientific source of information on tooth extraction?

Journal of Oral and Maxillofacial Surgery Medicine and Pathology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

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Using Large Language Models in the Diagnosis of Acute Cholecystitis: Assessing Accuracy and Guidelines Compliance

The American Surgeon, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Background Large language models (LLMs) are advanced tools capable of understanding and generating human-like text. This study evaluated the accuracy several commercial LLMs in addressing clinical questions related to diagnosis management acute cholecystitis, as outlined Tokyo Guidelines 2018 (TG18). We assessed their congruence with expert panel discussions presented guidelines. Methods ChatGPT4.0, Gemini Advanced, GPTo1-preview on ten questions. Eight derived from TG18, two were formulated by authors. Two authors independently rated each LLM’s responses a four-point scale: (1) accurate comprehensive, (2) but not (3) partially accurate, inaccurate, (4) entirely inaccurate. A third author resolved any scoring discrepancies. Then, we comparatively analyzed performance ChatGPT4.0 against newer large (LLMs), specifically Advanced GPTo1-preview, same set delineate respective strengths limitations. Results provided consistent for 90% It delivered “accurate comprehensive” answers 4/10 (40%) 5/10 (50%). One response (10%) was “partially inaccurate.” demonstrated higher some yielded similar percentage inaccurate” responses. Notably, neither model produced “entirely answers. Discussion LLMs, such ChatGPT demonstrate potential accurately regarding cholecystitis. With awareness limitations, careful implementation, ongoing refinement, could serve valuable resources physician education patient information, potentially improving decision-making future.

Language: Английский

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Advanced deep learning and large language models: Comprehensive insights for cancer detection

Image and Vision Computing, Journal Year: 2025, Volume and Issue: unknown, P. 105495 - 105495

Published: March 1, 2025

Language: Английский

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AI-driven patient support: Evaluating the effectiveness of ChatGPT-4 in addressing queries about ovarian cancer compared with healthcare professionals in gynecologic oncology

Supportive Care in Cancer, Journal Year: 2025, Volume and Issue: 33(4)

Published: April 1, 2025

Language: Английский

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A comparison of the responses between ChatGPT and doctors in the field of cholelithiasis based on clinical practice guidelines: a cross-sectional study

Digital Health, Journal Year: 2025, Volume and Issue: 11

Published: April 1, 2025

Background With the development of information age, an increasing number patients are seeking about related diseases on Internet. In medical field, several studies have confirmed that ChatGPT has great potential for use in education, generating imaging reports, and even providing clinical diagnosis treatment decisions, but its ability to answer questions gallstones not yet been reported literature. Objective The aim this study was evaluate consistency accuracy ChatGPT-generated answers cholelithiasis, compared provided by expert. Methods This designs task based practice guidelines cholelithiasis. presented form keywords. categorized into general professional questions. To performance expert answers, employs a modified matching scoring system, keyword proportion evaluation DISCERN tool. Results often provides more keywords responses, is significantly lower than doctors ( P < .001). 33 questions, demonstrated similar both score system = .856 .829, respectively). However, 32 consistently outperformed .004 .016). Additionally, while tool showed differences between .001), types were evaluated at high level overall. Conclusions Currently, performs similarly experts answering it cannot replace decision-making. As ChatGPT's improves through deep learning, expected become useful effective field Nevertheless, specialized areas, careful attention continuous will be necessary ensure accuracy, reliability, safety field.

Language: Английский

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