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Evaluation of ChatGPT-4 as an Online Outpatient Assistant in Puerperal Mastitis Management: Content Analysis of an Observational Study

Evaluation of ChatGPT-4 as an Online Outpatient Assistant in Puerperal Mastitis Management: Content Analysis of an Observational Study

AI-generated data has shown precise detection of osteoarthritis, though technical support is still necessary for some specific questions [14]. Data regarding urothelial carcinoma from AI are currently limited, with reliable information mainly focused on the epidemiology and risk factors [15]. In breast cancer oncology treatment, AI offers restricted insights into particular clinical scenarios and postoperative conditions [16].

Fatih Dolu, Oğuzhan Fatih Ay, Aydın Hakan Kupeli, Enes Karademir, Muhammed Huseyin Büyükavcı

JMIR Med Inform 2025;13:e68980

Design and Validation of a Chatbot-Based Cervical Cancer Screening Decision Aid for Women Experiencing Socioeconomic Disadvantage: User-Centered Approach Study

Design and Validation of a Chatbot-Based Cervical Cancer Screening Decision Aid for Women Experiencing Socioeconomic Disadvantage: User-Centered Approach Study

Numerous artificial intelligence (AI)–based chatbots have been developed to provide cancer screening education, and several studies have demonstrated that users readily embrace these tools, which can serve as an additional source of information for individuals who may struggle to obtain or understand health-related guidance [13].

Alice Le Bonniec, Catherine Sauvaget, Eric Lucas, Abdelhak Nassiri, Farida Selmouni

JMIR Cancer 2025;11:e70251

Improving Large Language Models’ Summarization Accuracy by Adding Highlights to Discharge Notes: Comparative Evaluation

Improving Large Language Models’ Summarization Accuracy by Adding Highlights to Discharge Notes: Comparative Evaluation

Their methodology involved prompting Chat GPT to create summaries and then having physicians assess the quality, accuracy, and bias of these summaries, where bias refers to the phenomenon where artificial intelligence (AI) systems are trained on data that lack sufficient reflection of the diversity within the population. The results showed that Chat GPT-produced summaries were 70% shorter than the original abstracts but maintained an accuracy of 92.5%.

Mahshad Koohi Habibi Dehkordi, Yehoshua Perl, Fadi P Deek, Zhe He, Vipina K Keloth, Hao Liu, Gai Elhanan, Andrew J Einstein

JMIR Med Inform 2025;13:e66476

Evaluating the Usability, Technical Performance, and Accuracy of Artificial Intelligence Scribes for Primary Care: Competitive Analysis

Evaluating the Usability, Technical Performance, and Accuracy of Artificial Intelligence Scribes for Primary Care: Competitive Analysis

A total of 6 AI scribes were selected for evaluation based on their market availability and compliance with data privacy and security regulations in Ontario (ie, PHIPA). To highlight the general capabilities of AI scribes, specific product names are not used; however, when referring to a particular AI scribe product, they are labeled as AI scribes #1 through #6. Table 1 provides an overview of the health care sectors and users for each of the AI scribes.

Emily Ha, Isabelle Choon-Kon-Yune, LaShawn Murray, Siying Luan, Enid Montague, Onil Bhattacharyya, Payal Agarwal

JMIR Hum Factors 2025;12:e71434

Exploring the Dilemma of AI Use in Medical Research and Knowledge Synthesis: A Perspective on Deep Research Tools

Exploring the Dilemma of AI Use in Medical Research and Knowledge Synthesis: A Perspective on Deep Research Tools

In addition, the AI tools’ inability to access paywalled literature introduces a potential bias toward open-access sources, which could affect the comprehensiveness and balance of the AI-generated output. Overall, expert readers were impressed by the results but noted a lack of scientific depth and nuance—the elements that distinguish strong review articles from mediocre ones.

Ariel Yuhan Ong, David A Merle, Siegfried K Wagner, Pearse A Keane

J Med Internet Res 2025;27:e75666

Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline

Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline

While there is no consensus on what AGI is, one may view an AGI system as a form of artificial intelligence (AI) with a general scope with the ability to perform well across various goals and contexts [17]. Finally, Yuan et al [82] provided a broad review of the applications and implications of LLMs in medicine, especially MLLMs, and discussed the emerging development of LLM-powered autonomous agents.

HongYi Li, Jun-Fen Fu, Andre Python

J Med Internet Res 2025;27:e71916

Identifying Psychosocial, Self-Management, and Health Profiles Among Women With Chronic Pain Who Have Experienced Intimate Partner Violence and Those Who Have Not: Protocol for a 2-Phase Qualitative and Cross-Sectional Study Using AI Techniques

Identifying Psychosocial, Self-Management, and Health Profiles Among Women With Chronic Pain Who Have Experienced Intimate Partner Violence and Those Who Have Not: Protocol for a 2-Phase Qualitative and Cross-Sectional Study Using AI Techniques

Machine learning, as a subset of artificial intelligence (AI) techniques, analyzes large datasets to identify patterns and make predictions [154]. These methods are transformative in gender studies, uncovering patterns in gender-related data and deepening the understanding of social inequalities and biases [155]. These methods have been successfully applied to areas such as forecasting gender-based violence, further demonstrating their relevance in social sciences [156].

Ainara Nardi-Rodríguez, Sónia Bernardes, María Ángeles Pastor-Mira, Sofía López-Roig, Lidia Pamies-Aubalat, Andrés Sánchez-Prada, Victoria A Ferrer-Pérez, Ignacio Rodríguez-Rodríguez, Purificación Heras-González

JMIR Res Protoc 2025;14:e66396

Improving AI-Based Clinical Decision Support Systems and Their Integration Into Care From the Perspective of Experts: Interview Study Among Different Stakeholders

Improving AI-Based Clinical Decision Support Systems and Their Integration Into Care From the Perspective of Experts: Interview Study Among Different Stakeholders

The literature describes a further wide range of problems and barriers in the context of AI-based CDSS [10-12]. These relate to AI or CDSS and a combination of both, AI-based CDSS. While some of the problems relate to technical integration and operational use [10,11], others relate to the legal and ethical framework [12].

Godwin Denk Giebel, Pascal Raszke, Hartmuth Nowak, Lars Palmowski, Michael Adamzik, Philipp Heinz, Marianne Tokic, Nina Timmesfeld, Frank Martin Brunkhorst, Jürgen Wasem, Nikola Blase

JMIR Med Inform 2025;13:e69688