From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare

Current Research in Biotechnology, Год журнала: 2023, Номер 7, С. 100164 - 100164

Опубликована: Ноя. 22, 2023

The medicine and healthcare sector has been evolving advancing very fast. advancement initiated shaped by the applications of data-driven, robust, efficient machine learning (ML) to deep (DL) technologies. ML in medical is developing quickly, causing rapid progress, reshaping medicine, improving clinician patient experiences. technologies evolved into data-hungry DL approaches, which are more robust dealing with data. This article reviews some critical data-driven aspects intelligence field. In this direction, illustrated recent progress science using two categories: firstly, development data uses and, secondly, Chabot particularly on ChatGPT. Here, we discuss ML, DL, transition requirements from DL. To science, illustrate prospective studies image data, newly interpretation EMR or EHR, big personalized dataset shifts artificial (AI). Simultaneously, recently developed DL-enabled ChatGPT technology. Finally, summarize broad role significant challenges for implementing healthcare. overview paradigm shift will benefit researchers immensely.

Язык: Английский

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Generative Pre-Trained Transformer-Empowered Healthcare Conversations: Current Trends, Challenges, and Future Directions in Large Language Model-Enabled Medical Chatbots

BioMedInformatics, Год журнала: 2024, Номер 4(1), С. 837 - 852

Опубликована: Март 14, 2024

This review explores the transformative integration of artificial intelligence (AI) and healthcare through conversational AI leveraging Natural Language Processing (NLP). Focusing on Large Models (LLMs), this paper navigates various sections, commencing with an overview AI’s significance in role AI. It delves into fundamental NLP techniques, emphasizing their facilitation seamless conversations. Examining evolution LLMs within frameworks, discusses key models used healthcare, exploring advantages implementation challenges. Practical applications conversations, from patient-centric utilities like diagnosis treatment suggestions to provider support systems, are detailed. Ethical legal considerations, including patient privacy, ethical implications, regulatory compliance, addressed. The concludes by spotlighting current challenges, envisaging future trends, highlighting potential reshaping interactions.

Язык: Английский

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ChatGPT vs. web search for patient questions: what does ChatGPT do better?

European Archives of Oto-Rhino-Laryngology, Год журнала: 2024, Номер 281(6), С. 3219 - 3225

Опубликована: Фев. 28, 2024

Язык: Английский

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Can artificial intelligence models serve as patient information consultants in orthodontics?

BMC Medical Informatics and Decision Making, Год журнала: 2024, Номер 24(1)

Опубликована: Июль 29, 2024

To evaluate the accuracy, reliability, quality, and readability of responses generated by ChatGPT-3.5, ChatGPT-4, Gemini, Copilot in relation to orthodontic clear aligners. Frequently asked questions patients/laypersons about aligners on websites were identified using Google search tool these posed AI models. Responses assessed a five-point Likert scale for modified DISCERN Global Quality Scale (GQS) Flesch Reading Ease Score (FRES) readability. ChatGPT-4 had highest mean score (4.5 ± 0.61), followed (4.35 0.81), ChatGPT-3.5 (4.15 0.75) Gemini (4.1 0.72). The difference between scores chatbot models was not statistically significant (p > 0.05). significantly higher GQS compared both < Gemini's than also FRES 38.39 11.56 43.88 10.13 41.72 10.74 Copilot, indicating that difficult read according reading level. is 54.12 10.27, are more readable other chatbots. All provided generally accurate, moderate reliable good quality answers Furthermore, difficult. ChatGPT, have potential as patient information tools orthodontics, however, be fully effective they need supplemented with evidence-based improved

Язык: Английский

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Assessing the role of advanced artificial intelligence as a tool in multidisciplinary tumor board decision-making for primary head and neck cancer cases

Frontiers in Oncology, Год журнала: 2024, Номер 14

Опубликована: Май 24, 2024

Background Head and neck squamous cell carcinoma (HNSCC) is a complex malignancy that requires multidisciplinary approach in clinical practice, especially tumor board discussions. In recent years, artificial intelligence has emerged as tool to assist healthcare professionals making informed decisions. This study investigates the application of ChatGPT 3.5 4.0, natural language processing models, decision-making. Methods We conducted pilot October 2023 on 20 consecutive head cancer patients discussed our (MDT). Patients with primary diagnosis were included. The MDT 4.0 recommendations for each patient compared by two independent reviewers number therapy options, recommendation, explanation summarization graded. Results this study, provided mostly general answers surgery, chemotherapy, radiation therapy. For scored well, but demonstrated be an assisting tool, suggesting significantly more options than MDT, while some recommended treatment modalities like immunotherapy are not part current guidelines. Conclusions research demonstrates advanced AI models at moment can merely setting, since versions list common sometimes recommend incorrect case lack information source material.

Язык: Английский

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Assessing the use of the novel tool Claude 3 in comparison to ChatGPT 4.0 as an artificial intelligence tool in the diagnosis and therapy of primary head and neck cancer cases

European Archives of Oto-Rhino-Laryngology, Год журнала: 2024, Номер 281(11), С. 6099 - 6109

Опубликована: Авг. 7, 2024

Head and neck squamous cell carcinoma (HNSCC) is a complex malignancy that requires multidisciplinary tumor board approach for individual treatment planning. In recent years, artificial intelligence tools have emerged to assist healthcare professionals in making informed decisions. This study investigates the application of newly published LLM Claude 3 Opus compared currently most advanced ChatGPT 4.0 diagnosis therapy planning primary HNSCC. The results were conventional board; (2) Materials Methods: We conducted March 2024 on 50 consecutive head cancer cases. diagnostics MDT recommendations each patient rated by two independent reviewers following parameters: clinical recommendation, explanation, summarization addition Artificial Intelligence Performance Instrument (AIPI); (3) Results: this study, achieved better scores diagnostic workup patients than provided involving surgery, chemotherapy, radiation therapy. terms recommendations, explanation scored similar 4.0, listing which congruent with MDT, but failed cite source information; (4) Conclusion: first analysis cases demonstrates superior performance HNSCC recommendations. marks advent launched AI model may be assessment setting.

Язык: Английский

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AI Chatbots for Mental Health: A Scoping Review of Effectiveness, Feasibility, and Applications

Applied Sciences, Год журнала: 2024, Номер 14(13), С. 5889 - 5889

Опубликована: Июль 5, 2024

Mental health disorders are a leading cause of disability worldwide, and there is global shortage mental professionals. AI chatbots have emerged as potential solution, offering accessible scalable interventions. This study aimed to conduct scoping review evaluate the effectiveness feasibility in treating conditions. A literature search was conducted across multiple databases, including MEDLINE, Scopus, PsycNet, well using AI-powered tools like Microsoft Copilot Consensus. Relevant studies on chatbot interventions for were selected based predefined inclusion exclusion criteria. Data extraction quality assessment performed independently by reviewers. The yielded 15 eligible covering various application areas, such support during COVID-19, specific conditions (e.g., depression, anxiety, substance use disorders), preventive care, promotion, usability assessments. demonstrated benefits improving emotional well-being, addressing conditions, facilitating behavior change. However, challenges related usability, engagement, integration with existing healthcare systems identified. hold promise interventions, but widespread adoption hinges systems. Enhancing personalization context-specific adaptation key. Future research should focus large-scale trials, optimal human–AI integration, ethical social implications.

Язык: Английский

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Can Artificial Intelligence “Hold” a Dermoscope?—The Evaluation of an Artificial Intelligence Chatbot to Translate the Dermoscopic Language

Diagnostics, Год журнала: 2024, Номер 14(11), С. 1165 - 1165

Опубликована: Май 31, 2024

This survey represents the first endeavor to assess clarity of dermoscopic language by a chatbot, unveiling insights into interplay between dermatologists and AI systems within complexity language. Given complex, descriptive, metaphorical aspects language, subjective interpretations often emerge. The evaluated completeness diagnostic efficacy chatbot-generated reports, focusing on their role in facilitating accurate diagnoses educational opportunities for novice dermatologists. A total 30 participants were presented with hypothetical descriptions skin lesions, including cancers such as BCC, SCC, melanoma, cancer mimickers actinic seborrheic keratosis, dermatofibroma, atypical nevus, inflammatory dermatosis psoriasis alopecia areata. Each description was accompanied specific clinical information, tasked assessing differential diagnosis list generated chatbot its initial response. In each scenario, an extensive potential diagnoses, exhibiting lower performance cases SCC dermatoses, albeit without statistical significance, suggesting that equally satisfied responses provided. Scores decreased notably when practical signs Answers BCC scenario scores category (2.9 ± 0.4) higher than those (2.6 0.66,

Язык: Английский

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The changing scenario of drug discovery using AI to deep learning: Recent advancement, success stories, collaborations, and challenges

Molecular Therapy — Nucleic Acids, Год журнала: 2024, Номер 35(3), С. 102295 - 102295

Опубликована: Авг. 8, 2024

Due to the transformation of artificial intelligence (AI) tools and technologies, AI-driven drug discovery has come forefront. It reduces time expenditure. these advantages, pharmaceutical industries are concentrating on discovery. Several molecules have been discovered using AI-based techniques tools, several newly AI-discovered already entered clinical trials. In this review, we first present data their resources in sector for illustrated some significant algorithms or used AI ML which field. We gave an overview deep neural network (NN) models compared them with NNs. Then, illustrate recent advancement landscape learning, such as identification targets, prediction structure, estimation drug-target interaction, binding affinity, design

Язык: Английский

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

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 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.

Язык: Английский

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