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April 18, 2017; 88 (16 Supplement) April 24, 2017

Computer algorithm as a supporting tool for clinical decision making on a mobile platform (P2.054)

Pulikottil Vinny, Venugopalan Vishnu, Neeraj Balaini, Manish Modi, Bishan Radotra, Vivek Lal
First published April 17, 2017,
Pulikottil Vinny
1Neurology, INHS Asvini Mumbai India
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Venugopalan Vishnu
2Neurology, PGIMER, CHANDIGARH Chandigarh India
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Neeraj Balaini
3Neurology Chandigarh India
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Manish Modi
2Neurology, PGIMER, CHANDIGARH Chandigarh India
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Bishan Radotra
4Histopathology, PGIMER, Chandigarh Chandigarh India
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Vivek Lal
3Neurology Chandigarh India
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Citation
Computer algorithm as a supporting tool for clinical decision making on a mobile platform (P2.054)
Pulikottil Vinny, Venugopalan Vishnu, Neeraj Balaini, Manish Modi, Bishan Radotra, Vivek Lal
Neurology Apr 2017, 88 (16 Supplement) P2.054;

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Abstract

Objective: To test the effectiveness of a novel computer algorithm in generating correct differential diagnoses as a supporting tool in clinical decision-making

Background: Many computer based diagnostic algorithms to support clinical decision making have evolved over the past years. We (first two authors) have created a computer algorithm that has subsequently been made into an application (app) on iPhone platform (iOS). The algorithm generates a maximum of thirteen differential diagnoses in a descending order of probability, based on clinical and radiological inputs by the user. The algorithm resides on iPhone as a standalone application and does not need any external resource including Internet to compute differential diagnoses.

Design/Methods: We compared the differentials generated by the algorithm with clinical and pathological diagnoses in a series of autopsy/biopsy proven cases. Towards this end we used 100 previously published NEJM ‘Case records of the Massachusetts General Hospital’ and 30 unpublished Clinico-Pathologic Conference cases(CPC) from Postgraduate Institute of Medical Education and Research(PGIMER), Chandigarh, India. In each case record, we tabulated key symptoms, signs, MRI features, clinical discussant’s differentials and final diagnoses. The key symptoms, signs and MRI features were used as inputs for the algorithm. The differential diagnoses computed by the algorithm were then compared with the differentials of the clinical discussant and the final autopsy/biopsy diagnoses.

Results: Our algorithm correctly identified final diagnosis in 82% of NEJM case records and 89% of PGIMER CPCs. We then compared the differentials of clinical discussant with that of our algorithm. The algorithm, in 76% of NEJM cases and 82% in PGIMER CPCs, also generated the differentials put forward by the clinical discussant.

Conclusions: Smart algorithms coupled with a massive computing power, can be a powerful tool at the hands of a budding neurologist. Our app harnesses this concept on a readily available mobile platform (iOS) with satisfactory results.

Disclosure: Dr. Vinny has nothing to disclose. Dr. Vishnu has nothing to disclose. Dr. Balaini has nothing to disclose. Dr. Modi has nothing to disclose. Dr. Radotra has nothing to disclose. Dr. Lal has nothing to disclose.

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