Decoding ChatGPT: A taxonomy of existing research, current challenges, and possible future directions

Sohail, Shahab Saquib; Farhat, Faiza; Himeur, Yassine; Nadeem, Mohammad; Madsen, Dag Øivind; Singh, Yashbir; Atalla, Shadi; Mansoor, Wathiq

doi:10.1016/j.jksuci.2023.101675

Cited by 59 publications

(14 citation statements)

References 158 publications

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“…Ensure responsible data practices and mitigate potential biases in network analysis [109]. Promote fairness and inclusivity in the application of network analysis.…”

Section: Ethical Considerationsmentioning

confidence: 99%

Exploring the Molecular Terrain: A Survey of Analytical Methods for Biological Network Analysis

Nguyen,

Dao,

Pham

et al. 2024

Symmetry

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Biological systems, characterized by their complex interplay of symmetry and asymmetry, operate through intricate networks of interacting molecules, weaving the elaborate tapestry of life. The exploration of these networks, aptly termed the “molecular terrain”, is pivotal for unlocking the mysteries of biological processes and spearheading the development of innovative therapeutic strategies. This review embarks on a comprehensive survey of the analytical methods employed in biological network analysis, focusing on elucidating the roles of symmetry and asymmetry within these networks. By highlighting their strengths, limitations, and potential applications, we delve into methods for network reconstruction, topological analysis with an emphasis on symmetry detection, and the examination of network dynamics, which together reveal the nuanced balance between stable, symmetrical configurations and the dynamic, asymmetrical shifts that underpin biological functionality. This review equips researchers with a multifaceted toolbox designed to navigate and decipher biological networks’ intricate, balanced landscape, thereby advancing our understanding and manipulation of complex biological systems. Through this detailed exploration, we aim to foster significant advancements in biological network analysis, paving the way for novel therapeutic interventions and a deeper comprehension of the molecular underpinnings of life.

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“…Ensure responsible data practices and mitigate potential biases in network analysis [109]. Promote fairness and inclusivity in the application of network analysis.…”

Section: Ethical Considerationsmentioning

confidence: 99%

Exploring the Molecular Terrain: A Survey of Analytical Methods for Biological Network Analysis

Nguyen,

Dao,

Pham

et al. 2024

Symmetry

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“…One notable advantage is the potential enhancement of the virtual tutoring system through personalized support for students. By leveraging ChatGPT as a virtual tutor, students can receive tailored explanations, translations, or verification of artifacts, thereby improving their fundamental understanding of specific topics (Sohail, Farhat, Himeur, Nadeem, Madsen, Singh & Mansoor, 2023;Neumann et al, 2023). Furthermore, the innovation potential of generative AI tools like ChatGPT presents opportunities for introducing novel teaching approaches and strategies.…”

Section: Emerging Challenges and Benefits Of Generative Ai Chatbots I...mentioning

confidence: 99%

Conceptual Framework for the Psychosocial Management of Depression in Adolescents in the North West Province, South Africa

2022

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“…In the mental health domain, ChatGPT has been employed for a variety of applications [15][16][17], and was able to identify a single patient with schizophrenia and recommend a treatment that aligns with current clinical standards of care [18]. Chat-GPT (GPT-3.5 and GPT-4) has shown significant language processing capabilities in the realm of mental health analysis.…”

Section: Introductionmentioning

confidence: 99%

ChatGPT Demonstrates Potential for Identifying Psychiatric Disorders: Application to Childbirth-Related Post-Traumatic Stress Disorder

Bartal,

Jagodnik,

Chan

et al. 2024

Preprint

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Free-text analysis using Machine Learning (ML)-based Natural Language Processing (NLP) shows promise for diagnosing psychiatric conditions. Chat Generative Pre-trained Transformer (ChatGPT) has demonstrated preliminary initial feasibility for this purpose; however, whether it can accurately assess mental illness remains to be determined. This study evaluates the effectiveness of ChatGPT and the text-embedding-ada-002 (ADA) model in detecting post-traumatic stress disorder following childbirth (CB-PTSD), a maternal postpartum mental illness affecting millions of women annually, with no standard screening protocol. Using a sample of 1,295 women who gave birth in the last six months and were 18 + years old, recruited through hospital announcements, social media, and professional organizations, we explore ChatGPT’s and ADA’s potential to screen for CB-PTSD by analyzing maternal childbirth narratives only. The PTSD Checklist for DSM-5 (PCL-5; cutoff 31) was used to assess CB-PTSD. By developing an ML model that utilizes numerical vector representation of the ADA model, we identify CB-PTSD via narrative classification. Our model outperformed (F1 score: 0.82) ChatGPT and six previously published large language models (LLMs) trained on mental health or clinical domains data, suggesting that the ADA model can be harnessed to identify CB-PTSD. Our modeling approach could be generalized to assess other mental health disorders. 1

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Decoding ChatGPT: A taxonomy of existing research, current challenges, and possible future directions

Cited by 59 publications

References 158 publications

Exploring the Molecular Terrain: A Survey of Analytical Methods for Biological Network Analysis

Exploring the Molecular Terrain: A Survey of Analytical Methods for Biological Network Analysis

Conceptual Framework for the Psychosocial Management of Depression in Adolescents in the North West Province, South Africa

ChatGPT Demonstrates Potential for Identifying Psychiatric Disorders: Application to Childbirth-Related Post-Traumatic Stress Disorder

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