Can large language models provide secondary reliable opinion on treatment options for dermatological diseases?

Objective: To investigate the consistency and reliability of medication recommendations provided by ChatGPT for common dermatological conditions, highlighting the potential for ChatGPT to offer second opinions in patient treatment while also delineating possible limitations.

Materials And Methods: In this mixed-methods study, we used survey questions in April 2023 for drug recommendations generated by ChatGPT with data from secondary databases, that is, Taiwan's National Health Insurance Research Database and an US medical center database, and validated by dermatologists. The methodology included preprocessing queries, executing them multiple times, and evaluating ChatGPT responses against the databases and dermatologists.

Facial Mimicry and Doctor-Patient Satisfaction: The Feasibility of Artificial Empathy in a Clinical Video Data.

Good nonverbal communication between doctor and patient is essential for achieving a successful and therapeutic doctor-patient relationship. Increasing evidence has shown that nonverbal communication mimicry, particularly facial mimicry, where one mirrors another's facial expressions, is linked to empathy and emotion recognition. Empathy is also the key driver of patient satisfaction.

Emotion recognition in doctor-patient interactions from real-world clinical video database: Initial development of artificial empathy.

Background And Objective: The promising use of artificial intelligence (AI) to emulate human empathy may help a physician engage with a more empathic doctor-patient relationship. This study demonstrates the application of artificial empathy based on facial emotion recognition to evaluate doctor-patient relationships in clinical practice.

Methods: A prospective study used recorded video data of doctor-patient clinical encounters in dermatology outpatient clinics, Taipei Municipal Wanfang Hospital, and Taipei Medical University Hospital collected from March to December 2019.

SlimMe, a Chatbot With Artificial Empathy for Personal Weight Management: System Design and Finding.

As the obesity rate continues to increase persistently, there is an urgent need to develop an effective weight loss management strategy. Nowadays, the development of artificial intelligence (AI) and cognitive technologies coupled with the rapid spread of messaging platforms and mobile technology with easier access to internet technology offers professional dietitians an opportunity to provide extensive monitoring support to their clients through a chatbot with artificial empathy. This study aimed to design a chatbot with artificial empathic motivational support for weight loss called "SlimMe" and investigate how people react to a diet bot.

Social media sentiment analysis to monitor the performance of vaccination coverage during the early phase of the national COVID-19 vaccine rollout.

Background And Objective: Social media sentiment analysis based on Twitter data can facilitate real-time monitoring of COVID-19 vaccine-related concerns. Thus, the governments can adopt proactive measures to address misinformation and inappropriate behaviors surrounding the COVID-19 vaccine, threatening the success of the national vaccination campaign. This study aims to identify the correlation between COVID-19 vaccine sentiments expressed on Twitter and COVID-19 vaccination coverage, case increase, and case fatality rate in Indonesia.

Chemopreventive Effects of Concomitant or Individual Use of Statins, Aspirin, Metformin, and Angiotensin Drugs: A Study Using Claims Data of 23 Million Individuals.

Despite previous studies on statins, aspirin, metformin, and angiotensin-converting-enzyme inhibitors (ACEIs)/angiotensin II receptor blockers (ARBs), little has been studied about all their possible combinations for chemoprevention against cancers. This study aimed to comprehensively analyze the composite chemopreventive effects of all the combinations. In this case-control study, health records were retrieved from claims databases of Taiwan's Health and Welfare Data Science Center.

How Can Research on Artificial Empathy Be Enhanced by Applying Deepfakes?

We propose the idea of using an open data set of doctor-patient interactions to develop artificial empathy based on facial emotion recognition. Facial emotion recognition allows a doctor to analyze patients' emotions, so that they can reach out to their patients through empathic care. However, face recognition data sets are often difficult to acquire; many researchers struggle with small samples of face recognition data sets.

Voice-based control system for smart hospital wards: a pilot study of patient acceptance.

Background: The smart hospital's concept of using the Internet of Things (IoT) to reduce human resources demand has become more popular in the aging society.

Objective: To implement the voice smart care (VSC) system in hospital wards and explore patient acceptance via the Technology Acceptance Model (TAM).

Methods: A structured questionnaire based on TAM was developed and validated as a research tool.

Social Media Data Analytics for Outbreak Risk Communication: Public Attention on the "New Normal" During the COVID-19 Pandemic in Indonesia.

Background: After two months of implementing a partial lockdown, the Indonesian government had announced the "New Normal" policy to prevent a further economic crash in the country. This policy received many critics, as Indonesia still experiencing a fluctuated number of infected cases. Understanding public perception through effective risk communication can assist the government in relaying an appropriate message to improve people's compliance and to avoid further disease spread.

Alumni's perception of public health informatics competencies: lessons from the Graduate Program of Public Health, Faculty of Medicine, Universitas Gadjah Mada, Indonesia.

Public health informatics has been defined as the systematic application of information and computer science and technology to public health practice, research, and learning [1]. Unfortunately, limited reports exist concerning to the capacity building strategies to improve public health informatics workforce in limited-resources setting. In Indonesia, only three universities, including Universitas Gadjah Mada (UGM), offer master degree program on related public health informatics discipline.