Android App Solutions to Aid Clinical Decision-Making

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Akanksha Srivastava, Akash Ranjan Das, Rakshitha B, Shruthi K


One of the key challenges today faced by the healthcare system is the retrieval and analysis of huge quantities of varying data for various use cases such as clinical care, screening test, administration, and research. With the concept of learning the healthcare system cycle, clinical research and practice both can become a distinctive and cooperative process. Clinical decision support systems need to aid entailment within events by updating and modeling accordingly the various details of clinical care. Well-designed and precise models of clinical regulations and care pathways can be a successful tool to distinguish the analytic results from anticipated behaviors. In this paper, we are introducing an android app for clinical decision-making for nursing students, nursing practitioners, and patients in order to make the diagnosis more accurate, easy, and cost-effective. The app gives two separate UI for patients and nursing practitioners. It uses the symptoms of potential patients as inputs, gives the diagnostic results to the nursing practitioner, and suggests local doctors to the patients, using machine learning algorithms. This could permit constructive revision of continuously collected data, to acquire a new understanding of patients’ results, and to give reasons for their clinical patterns. All these measures are the solutions of a Learning Health Care System that we implement as an Android Application.

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