Ethical Considerations of Using ChatGPT in Health Care

Journal of Medical Internet Research, Год журнала: 2023, Номер 25, С. e48009 - e48009

Опубликована: Июль 25, 2023

ChatGPT has promising applications in health care, but potential ethical issues need to be addressed proactively prevent harm. presents challenges from legal, humanistic, algorithmic, and informational perspectives. Legal ethics concerns arise the unclear allocation of responsibility when patient harm occurs breaches privacy due data collection. Clear rules legal boundaries are needed properly allocate liability protect users. Humanistic disruption physician-patient relationship, humanistic integrity. Overreliance on artificial intelligence (AI) can undermine compassion erode trust. Transparency disclosure AI-generated content critical maintaining Algorithmic raise about algorithmic bias, responsibility, transparency explainability, as well validation evaluation. Information include validity, effectiveness. Biased training lead biased output, overreliance reduce adherence encourage self-diagnosis. Ensuring accuracy, reliability, validity ChatGPT-generated requires rigorous ongoing updates based clinical practice. To navigate evolving landscape AI, AI care must adhere strictest standards. Through comprehensive guidelines, professionals ensure responsible use ChatGPT, promote accurate reliable information exchange, privacy, empower patients make informed decisions their care.

Язык: Английский

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Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation

Information Fusion, Год журнала: 2023, Номер 99, С. 101896 - 101896

Опубликована: Июнь 24, 2023

Trustworthy Artificial Intelligence (AI) is based on seven technical requirements sustained over three main pillars that should be met throughout the system's entire life cycle: it (1) lawful, (2) ethical, and (3) robust, both from a social perspective. However, attaining truly trustworthy AI concerns wider vision comprises trustworthiness of all processes actors are part cycle, considers previous aspects different lenses. A more holistic contemplates four essential axes: global principles for ethical use development AI-based systems, philosophical take ethics, risk-based approach to regulation, mentioned requirements. The (human agency oversight; robustness safety; privacy data governance; transparency; diversity, non-discrimination fairness; societal environmental wellbeing; accountability) analyzed triple perspective: What each requirement is, Why needed, How can implemented in practice. On other hand, practical implement systems allows defining concept responsibility facing law, through given auditing process. Therefore, responsible system resulting notion we introduce this work, utmost necessity realized processes, subject challenges posed by regulatory sandboxes. Our multidisciplinary culminates debate diverging views published lately about future AI. reflections matter conclude regulation key reaching consensus among these views, will crucial present our society.

Язык: Английский

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Evaluation of artificial intelligence techniques in disease diagnosis and prediction

Discover Artificial Intelligence, Год журнала: 2023, Номер 3(1)

Опубликована: Янв. 30, 2023

Abstract A broad range of medical diagnoses is based on analyzing disease images obtained through high-tech digital devices. The application artificial intelligence (AI) in the assessment has led to accurate evaluations being performed automatically, which turn reduced workload physicians, decreased errors and times diagnosis, improved performance prediction detection various diseases. AI techniques image processing are an essential area research that uses advanced computer algorithms for prediction, treatment planning, leading a remarkable impact decision-making procedures. Machine Learning (ML) Deep (DL) as two main subfields applied healthcare system diagnose diseases, discover medication, identify patient risk factors. advancement electronic records big data technologies recent years accompanied success ML DL algorithms. includes neural networks fuzzy logic with applications automating forecasting diagnosis processes. algorithm technique does not rely expert feature extraction, unlike classical network high-performance calculations give promising results analysis, such fusion, segmentation, recording, classification. Support Vector (SVM) method Convolutional Neural Network (CNN) usually most widely used diagnosing This review study aims cover predicting numerous diseases cancers, heart, lung, skin, genetic, disorders, perform more precisely compared specialists without human error. Also, AI's existing challenges limitations discussed highlighted.

Язык: Английский

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Harnessing the Power of AI: A Comprehensive Review of Its Impact and Challenges in Nursing Science and Healthcare

Cureus, Год журнала: 2023, Номер unknown

Опубликована: Ноя. 22, 2023

This comprehensive review delves into the impact and challenges of Artificial Intelligence (AI) in nursing science healthcare. AI has already demonstrated its transformative potential these fields, with applications spanning from personalized care diagnostic accuracy to predictive analytics telemedicine. However, integration complexities, including concerns related data privacy, ethical considerations, biases algorithms datasets. The future healthcare appears promising, poised advance diagnostics, treatment, practices. Nevertheless, it is crucial remember that should complement, not replace, professionals, preserving essential human element care. To maximize AI's healthcare, interdisciplinary collaboration, guidelines, protection patient rights are essential. concludes a call action, emphasizing need for ongoing research collective efforts ensure contributes improved outcomes while upholding highest standards ethics patient-centered

Язык: Английский

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Accuracy of ChatGPT‐Generated Information on Head and Neck and Oromaxillofacial Surgery: A Multicenter Collaborative Analysis

Otolaryngology, Год журнала: 2023, Номер 170(6), С. 1492 - 1503

Опубликована: Авг. 18, 2023

Abstract Objective To investigate the accuracy of Chat‐Based Generative Pre‐trained Transformer (ChatGPT) in answering questions and solving clinical scenarios head neck surgery. Study Design Observational valuative study. Setting Eighteen surgeons from 14 Italian surgery units. Methods A total 144 encompassing different subspecialities 15 comprehensive were developed. Questions inputted into ChatGPT4, resulting answers evaluated by researchers using (range 1‐6), completeness 1‐3), references' quality Likert scales. Results The overall median score open‐ended was 6 (interquartile range[IQR]: 5‐6) for 3 (IQR: 2‐3) completeness. Overall, reviewers rated answer as entirely or nearly correct 87.2% cases covering all aspects question 73% cases. artificial intelligence (AI) model achieved a response 84.7% closed‐ended (11 wrong answers). As scenarios, ChatGPT provided fully diagnosis 81.7% proposed diagnostic therapeutic procedure judged to be complete 56.7% bibliographic references poor, sources nonexistent 46.4% Conclusion results generally demonstrate good level AI's answers. ability resolve complex is promising, but it still falls short being considered reliable support decision‐making process specialists head‐neck

Язык: Английский

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Challenges and strategies for wide-scale artificial intelligence (AI) deployment in healthcare practices: A perspective for healthcare organizations

Artificial Intelligence in Medicine, Год журнала: 2024, Номер 151, С. 102861 - 102861

Опубликована: Март 30, 2024

Язык: Английский

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Accuracy and Completeness of ChatGPT-Generated Information on Interceptive Orthodontics: A Multicenter Collaborative Study

Journal of Clinical Medicine, Год журнала: 2024, Номер 13(3), С. 735 - 735

Опубликована: Янв. 27, 2024

: this study aims to investigate the accuracy and completeness of ChatGPT in answering questions solving clinical scenarios interceptive orthodontics.

Язык: Английский

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Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine

Journal of Translational Medicine, Год журнала: 2024, Номер 22(1)

Опубликована: Фев. 5, 2024

Abstract Advancements in data acquisition and computational methods are generating a large amount of heterogeneous biomedical from diagnostic domains such as clinical imaging, pathology, next-generation sequencing (NGS), which help characterize individual differences patients. However, this information needs to be available suitable promote support scientific research technological development, supporting the effective adoption precision medicine approach practice. Digital biobanks can catalyze process, facilitating sharing curated standardized imaging data, clinical, pathological molecular crucial enable development comprehensive personalized data-driven disease management fostering predictive models. This work aims frame perspective, first by evaluating state standardization then identifying challenges proposing possible solution towards an integrative that guarantee suitability shared through digital biobank. Our analysis art shows presence use reference standards and, generally, repositories for each specific domain. Despite this, integration reproducibility numerical descriptors generated domain, e.g. radiomic, pathomic -omic features, is still open challenge. Based on cases scenarios, model, based JSON format, proposed address problem. Ultimately, how, with promotion efforts, biobank model become enabling technology study diseases technologies at service medicine.

Язык: Английский

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Shaping the future of AI in healthcare through ethics and governance

Humanities and Social Sciences Communications, Год журнала: 2024, Номер 11(1)

Опубликована: Март 15, 2024

Abstract The purpose of this research is to identify and evaluate the technical, ethical regulatory challenges related use Artificial Intelligence (AI) in healthcare. potential applications AI healthcare seem limitless vary their nature scope, ranging from privacy, research, informed consent, patient autonomy, accountability, health equity, fairness, AI-based diagnostic algorithms care management through automation for specific manual activities reduce paperwork human error. main faced by states regulating were identified, especially legal voids complexities adequate regulation better transparency. A few recommendations made protect data, mitigate risks regulate more efficiently international cooperation adoption harmonized standards under World Health Organization (WHO) line with its constitutional mandate digital public health. European Union (EU) law can serve as a model guidance WHO reform International Regulations (IHR).

Язык: Английский

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Research on Artificial-Intelligence-Assisted Medicine: A Survey on Medical Artificial Intelligence

Diagnostics, Год журнала: 2024, Номер 14(14), С. 1472 - 1472

Опубликована: Июль 9, 2024

With the improvement of economic conditions and increase in living standards, people's attention regard to health is also continuously increasing. They are beginning place their hopes on machines, expecting artificial intelligence (AI) provide a more humanized medical environment personalized services, thus greatly expanding supply bridging gap between resource demand. development IoT technology, arrival 5G 6G communication era, enhancement computing capabilities particular, application AI-assisted healthcare have been further promoted. Currently, research field assistance deepening expanding. AI holds immense value has many potential applications institutions, patients, professionals. It ability enhance efficiency, reduce costs, improve quality intelligent service experience for professionals patients. This study elaborates history timelines field, types technologies informatics, opportunities challenges medicine. The combination profound impact human life, improving levels life changing lifestyles.

Язык: Английский

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