Translating Innovation in Diagnostics: Challenges and Opportunities

Brown, Matthew; Lai-Goldman, Myla; Billings, Paul R.

doi:10.1016/b978-0-12-369420-1.00031-7

Cited by 2 publications

(2 citation statements)

References 47 publications

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“…The molecular diagnostics company is supporting to pressure the in vitro diagnostic (IVD) company and the agencies involved. 11 Molecular diagnostics has enormous business power due to the fact that these controls are more effective at detecting viruses and infectious diseases, and they do so with a degree of confusion sooner than was previously possible. Personalized Medication now includes all controls that modify or personalize the remedy for a selected disorder in an affected person.…”

Section: Opportunitiesmentioning

confidence: 99%

Establishing PCR Testing in Nepal for Covid-19: Challenges and Opportunities

Khadka

Gyawali²

2020

Kathmandu Univ. Med. J.

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Polymerase chain reaction (PCR) invented by Kary Mullis (1983), has become the centrepiece of molecular detection of various infectious diseases including coronavirus disease 2019 (COVID-19). Many developing countries like Nepal faces various challenges and grab many future opportunities during and after establishment of molecular PCR laboratories throughout the country. This viewpoint describes the involvement of laboratory employees, development and adoption of new protocols or framework, deliberate partnership with national and international community is very efficient for the establishment of PCR laboratories. Beside this, continued alliance and nation leadership is crucial to generate a unified and sustainable PCR laboratory network in the country like Nepal. In future the established PCR laboratories can be utilized for the diagnosis of others pandemic diseases and can be used for multipurpose like in verification of infectious diseases; Oncology; Blood test; Genetic testing.

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Section: Opportunitiesmentioning

confidence: 99%

Establishing PCR Testing in Nepal for Covid-19: Challenges and Opportunities

Khadka

Gyawali²

2020

Kathmandu Univ. Med. J.

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“…For the past decade, medical knowledge and diagnostic techniques have expanded worldwide, becoming more accessible with remarkable advancements in clinical testing and useful reference systems [ 1 ]. Despite these advancements, misdiagnosis significantly contributes to mortality, making it a noteworthy public health issue [ 2 3 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of ChatGPT-Generated Differential Diagnosis for Common Diseases With Atypical Presentation: Descriptive Research

Shikino,

Shimizu,

Otsuka

et al. 2024

JMIR Med Educ

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Background The persistence of diagnostic errors, despite advances in medical knowledge and diagnostics, highlights the importance of understanding atypical disease presentations and their contribution to mortality and morbidity. Artificial intelligence (AI), particularly generative pre-trained transformers like GPT-4, holds promise for improving diagnostic accuracy, but requires further exploration in handling atypical presentations. Objective This study aimed to assess the diagnostic accuracy of ChatGPT in generating differential diagnoses for atypical presentations of common diseases, with a focus on the model’s reliance on patient history during the diagnostic process. Methods We used 25 clinical vignettes from the Journal of Generalist Medicine characterizing atypical manifestations of common diseases. Two general medicine physicians categorized the cases based on atypicality. ChatGPT was then used to generate differential diagnoses based on the clinical information provided. The concordance between AI-generated and final diagnoses was measured, with a focus on the top-ranked disease (top 1) and the top 5 differential diagnoses (top 5). Results ChatGPT’s diagnostic accuracy decreased with an increase in atypical presentation. For category 1 (C1) cases, the concordance rates were 17% (n=1) for the top 1 and 67% (n=4) for the top 5. Categories 3 (C3) and 4 (C4) showed a 0% concordance for top 1 and markedly lower rates for the top 5, indicating difficulties in handling highly atypical cases. The χ 2 test revealed no significant difference in the top 1 differential diagnosis accuracy between less atypical (C1+C2) and more atypical (C3+C4) groups ( χ ² 1 =2.07; n=25; P =.13). However, a significant difference was found in the top 5 analyses, with less atypical cases showing higher accuracy ( χ ² 1 =4.01; n=25; P =.048). Conclusions ChatGPT-4 demonstrates potential as an auxiliary tool for diagnosing typical and mildly atypical presentations of common diseases. However, its performance declines with greater atypicality. The study findings underscore the need for AI systems to encompass a broader range of linguistic capabilities, cultural understanding, and diverse clinical scenarios to improve diagnostic utility in real-world settings.

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Translating Innovation in Diagnostics: Challenges and Opportunities

Cited by 2 publications

References 47 publications

Establishing PCR Testing in Nepal for Covid-19: Challenges and Opportunities

Establishing PCR Testing in Nepal for Covid-19: Challenges and Opportunities

Evaluation of ChatGPT-Generated Differential Diagnosis for Common Diseases With Atypical Presentation: Descriptive Research

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