Application of artificial intelligence to corelate food formulations to disease risk prediction: a comprehensive review.

Clinicians and administrators are applying Artificial Intelligence (AI) Techniques widely as the promising results of their applications in the healthcare have been established. The meaningful impact of the AI applications will be limited unless it is coherently applied with human diagnosis and inputs from specialist clinician. This will help to address limitations and take advantage of the promises of the AI techniques. Machine Learning is one of the AI technique that finds high relevance in the medicine and health care. This review provides an overall glimpse of current practices and research outcomes of the application of the AI techniques in the healthcare and medical practices. It further describes Machine Learning Techniques in disease prediction and scope for food formulations for combatting disease.

Development and validation of a comprehensive needs assessment tool to assess the burden of cancer chemotherapy patients attending a tertiary care hospital.

INTRODUCTION: In India in 2020, there were an estimated 1.39 million cancers present in the country. Chemotherapy patients experience several problems such as ADRs (adverse drug reactions), and because of this, many dropouts have been happening. Also, there is a lack of communication between the patient and care providers (doctors). OBJECTIVES: Development and validation of a comprehensive needs assessment tool to assess the burden of chemotherapy on patients attending tertiary level health care facilities. MATERIALS AND METHODS: Development and validation of comprehensive needs assessment in cancer chemotherapy involve several steps, including problem statement and literature review regarding the problem, domain generation, development of the preliminary questionnaire, face validation, statistical validation, and final draft of the tool. RESULTS: A total of 10 experts are involved in face validation. The majority (80%) of the experts agreed with the grammar, clarity, and content of the tool. A few experts (20%) disagreed regarding the construction of the questionnaire, the appropriate level of understanding for the participants, and the content of the tool and suggested changes in the physical and psychological domains. The questionnaire has been re-structured according to the expert's suggestion before going for statistical validation. Internal consistency of the CNAT-CC was optimal, with a satisfactory Cronbach's alpha of 0.7 for the total scale. DISCUSSION: The current study was focused on the development and validation of needs assessment in cancer chemotherapy patients. The CNAT-CC promises to be a comprehensive needs assessment tool that applies to a comparatively vast majority of patients undergoing cancer chemotherapy.

Validation of EURO-D, a geriatric depression scale in South India: Findings from the Mysore study of Natal effects on Ageing and Health (MYNAH).

INTRODUCTION: Many of the assessment tools used to study depression amongst older people in low- and middle- income countries (LMICs) are adaptations of instruments developed in other cultural settings. There is a need to validate those instruments in LMICs. METHODS: 721 men and women aged 55-80 years from the Mysore Birth Records Cohort underwent standardised assessments for sociodemographic characteristics, cardiometabolic risk factors, cognitive function and mental health. Sensitivity, specificity and level of agreement of EURO-D diagnosis of depression with diagnosis of depression derived by the Geriatric Mental State (GMS) examination were calculated. To validate the EURO-D score against GMS depressive episode, we used maximum Youden's index as the criterion for each cut-off point. Concurrent validity was assessed by measuring correlations with the WHO Disability Assessment Schedule (WHO DAS II). RESULTS: Of the 721 (408 men and 313 women) who participated in this study, 138 (54 men and 84 women) were diagnosed with depression. Women had higher depression scores on the EURO-D scale and disability on the WHO DAS II scale. A maximum Youden's Index of 0.60 was observed at a EURO-D cut-off of 6, which corresponded to 95% sensitivity, 64% specificity, kappa value of 0.6 and area under the curve (AUC) of 80%. There was significant and positive correlation between EURO-D and WHO DAS II scores. LIMITATIONS: Future independent validation studies in other settings are required. DISCUSSION: This study supports the use of the EURO-D scale for diagnosing depression amongst older adults in South India.

An android smartphone-based randomized intervention improves the quality of life in patients with type 2 diabetes in Mysore, Karnataka, India.

BACKGROUND AND AIMS: Associated with severe complications and morbidity, Diabetes Mellitus is a significant public health burden. The need for regular monitoring and adherence to treatment and lifestyle changes have a high impact on the quality of life of the patients. This study attempts to assess the effect of smartphone-based lifestyle modification intervention in the quality of life of patients with type 2 Diabetes through a randomized filed trial. METHODS: A randomized field trial was performed among the patients attending the outpatient department of a tertiary care hospital in Mysuru city. A mobile application named DIAGURU, mainly focusing on the lifestyle modification and medication management was used for a period of 6 months from April 2019 to September 2019 by 150 patients in the intervention group while another 150 participants served as controls. The quality of life was assessed using the WHO QOL BREF questionnaire at the beginning of the study and after six months. RESULTS: The change in the quality of life in a positive direction was significantly higher in the intervention group compared to the non-intervention group after six months. The differences in the change in scores of quality of life of participants recruited in intervention and non-intervention groups were statistically significant in all the four domains after the intervention with a p value < 0.001. CONCLUSION: The evidence generated in this study suggest that such technological approaches can be used as a public health measure to improve the quality of life of patients with type 2 Diabetes Mellitus.