Missing data imputation on biomedical data using deeply learned clustering and L2 regularized regression based on symmetric uncertainty.

Big data era in healthcare led to the generation of high dimensional datasets like genomic datasets, electronic health records etc. One among the critical issues to be addressed in such datasets is handling incomplete data that may yield misleading results if not handled properly. Imputation is considered to be an effective way when the missing data rate is high.

A hybrid feature selection model based on improved squirrel search algorithm and rank aggregation using fuzzy techniques for biomedical data classification.

Feature selection has gained its importance due to the voluminous nature of the data. Owing to the computational complexity of wrapper approaches, the poor performance of filtering techniques, and the classifier dependency of embedded approaches, hybrid approaches are more commonly used in feature selection. Hybrid approaches use filtering metrics to reduce the computational complexity of wrapper algorithms and are proved to yield better feature subset.

Patient and Public Involvement for Dementia Research in Low- and Middle-Income Countries: Developing Capacity and Capability in South Asia.

Patient and public involvement (PPI) is an active partnership between the public and researchers in the research process. In dementia research, PPI ensures that the perspectives of the person with "lived experience" of dementia are considered. To date, in many lower- and middle-income countries (LMIC), where dementia research is still developing, PPI is not well-known nor regularly undertaken.

Cultural adaptation of Alzheimer's disease assessment scale-cognitive subscale for use in India and validation of the Tamil version for South Indian population.

Objective: Currently no standardized tools are available in the Indian languages to assess changes in cognition. Our objectives are to culturally adapt the Alzheimer's disease Assessment Scale-Cognitive Subscale (ADAS-Cog) for use in India and to validate the Tamil version in an urban Tamil-speaking older adult population.

Methods: Two panels of key stakeholders and a series of qualitative interviews informed the cultural and linguistic adaptation of the ADAS-Cog-Tamil.

A hybrid of whale optimization and late acceptance hill climbing based imputation to enhance classification performance in electronic health records.

Electronic health records (EHR) are a major source of information in biomedical informatics. Yet, missing values are prominent characteristics of EHR. Prediction on dataset with missing values results in inaccurate inferences.