Generative Artificial Intelligence-based Treatment Planning in Patient Consultation and Support, in Digital Health Interventions, and in Medical Practice and Education.

• Author: Atkinson, Diana

1. Introduction

   Generative artificial intelligence tools (Balcerzak et al, 2022; Lazaroiu et al, 2020; Newell, 2022) can produce clinical documentation and medical reports swiftly and improve diagnosis, treatment planning, and disease accuracy and efficiency. The purpose of my systematic review is to examine the recently published literature on generative artificial intelligence-based treatment planning and integrate the insights it configures on patient consultation and support, on digital health interventions, and on medical practice and education. By analyzing the most recent (2023) and significant (Web of Science, Scopus, and ProQuest) sources, my paper has attempted to prove that generative artificial intelligence tools can optimize patient consultations, reduce administrative burdens, and provide personalized on-demand patient assistance. The actuality and novelty of this study are articulated by addressing how generative artificial intelligence technologies (Andronie et al., 2023; Glogovetan et al, 2022; Nica et al, 2023) can improve medical education by integrating immersive and contextually relevant (Barber, 2022; Lazaroiu et al., 2022; Peters et al., 2023; Popescu et al., 2017a) realistic healthcare simulations and providing personalized feedback to digital patients, that is an emerging topic involving much interest. My research problem is whether ChatGPT can manage intricate medical and clinical information in diagnosis, treatment planning, and patient outcome monitoring.

   In this review, prior findings have been cumulated indicating that generative artificial intelligence (Dabija et al, 2022; Nagy et al, 2023; Popescu, 2018; Watson, 2022) can optimize treatment decision making, predict adverse medical results, provide credible information for both physicians and patients, and reorganize perioperative healthcare management. The identified gaps advance how generative artificial intelligence algorithms can deploy visual information related to high-level decision-making questions (Barbu et al, 2021; Nagy and Lazaroiu, 2022; Popescu et al, 2017b) and produce consistent results in clinical applications. My main objective is to indicate that ChatGPT can be pivotal in healthcare services, in medical education processes, and in clinical reasoning tasks with regard to preventative measures and treatment options.

2. Theoretical Overview of the Main Concepts

   ChatGPT can optimize physician workflow, enable increased quality care and guidance, and analyze medical images and texts. ChatGPT can provide accurate, appropriate, and consistent medical recommendations by automated patient educational information provision, thus organizing healthcare education and counseling delivery. Synthetic data correspond to real clinical-genomic features and results, and de-identify patient data, optimizing precision medicine and clinical trial conduction through generative artificial intelligence. ChatGPT can provide treatment options and medical diagnoses, improve patient outcomes and clinical decision-making, and streamline patient monitoring. ChatGPT would significantly assist healthcare professionals by operating in real-world scenarios and in simulated cases through structured and objective evaluations, and by articulating real-time acute situation-related empathic and emotionally intelligent feedback. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), ChatGPT can articulate easily comprehended individual medical evaluations (section 4), generative artificial intelligence can optimize treatment decision making (section 5), ChatGPT can provide accurate, appropriate, and consistent medical recommendations (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10).

3. Methodology

   Throughout April 2023, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including "generative artificial intelligence-based treatment planning" + "patient consultation and support," "digital health interventions," and "medical practice and education." As I inspected research published in 2023, only 180 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 34, generally empirical, sources (Tables 1 and 2). Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, Distiller SR, and MMAT (Figures 1-6).

4. ChatGPT Can Articulate Easily Comprehended Individual Medical Evaluations

   Generative artificial intelligence tools can create interactive learning modules for virtual patients and can facilitate clinical communication skill practice and problem-solving task collaboration (Abd-alrazaq et al., 2023; D'Amico et al., 2023; Temsah et al., 2023) in medical training, assessments, and assignments. Synthetic data correspond to real clinical-genomic features and results, and de-identify patient data, optimizing precision medicine and clinical trial conduction through generative artificial intelligence.

   Supplementing healthcare professional expertise, ChatGPT can be integrated into electronic health record systems (Ali, 2023; Liu et al., 2023; Richu et al., 2023), optimizing diagnostic precision, clinical decision making, treatment planning, and patient outcomes, and articulating accurate differential diagnosis lists. Generative artificial intelligence tools can optimize patient consultations, reduce administrative burdens, and provide personalized on-demand patient assistance.

   Through algorithmic decision-making, ChatGPT can articulate easily comprehended individual medical evaluations and provide effective medical advice as coherent answers considering patient objectives and sufficiently informed recovery process estimations in health-specific situations (Bassiri-Tehrani and Cress, 2023; Grunebaum et al., 2023; Levin et al., 2023; Xie et al., 2023), advancing digital clinical guidance and diagnostics. ChatGPT can manage intricate medical and clinical information in diagnosis, treatment planning, and patient outcome monitoring. (Table 3)

5. Generative Artificial Intelligence Can Optimize Treatment Decision Making

   ChatGPT would significantly assist healthcare professionals by operating in real-world scenarios and in simulated cases through structured and objective evaluations, and by articulating real-time acute situation-related empathic and emotionally intelligent feedback (Altamimi et al., 2023; Barat et al., 2023; Bhayana et al., 2023; Wu and Dang, 2023), thus generating streamlined artificial intelligence-assisted medical solutions. ChatGPT can optimize physician workflow, enable increased quality care and guidance, and analyze medical images and texts.

   Accurate, reliable, and reproducible responses, medical recommendations and standards of practice, and implementation processes articulated by ChatGPT can empower patients (Dubin et al., 2023; Lee, 2023; Samaan et al., 2023; Srijan Chatterjee et al., 2023), optimizing healthcare experiences and outcomes while assisting healthcare professionals. Generative artificial intelligence can optimize treatment decision making, predict adverse medical results, provide credible information for both physicians and patients, and reorganize perioperative healthcare...