Description

Machine learning is a type of artificial intelligence that allows computer systems to learn and improve on their own without being explicitly programmed. Supervised learning is a popular machine learning method in which a model is trained on labelled data to make predictions on new, unseen data. Obtaining labelled data, can be costly, time-consuming, and often difficult, particularly in domains such as healthcare.

Semi-supervised learning is a machine learning algorithm that trains a model using both labelled and unlabeled data. Labeled data informs the model about what the correct output should be, whereas labelless data improves the model's generalisation and robustness. Semi-supervised learning is frequently used when obtaining labelled data is difficult or impossible.

Use Of Semi-Supervised Learning For Healthcare Applications

The study on the prevalence of dementia in older adults in India demonstrates the utility of semi-supervised learning in healthcare applications. Healthcare data is frequently complex and heterogeneous, making it difficult to obtain labelled data due to privacy concerns and data regulations.

Semi-supervised learning can also be used to improve medical diagnosis, prediction, and prognosis accuracy and efficiency. It can, for example, aid in the identification of patients at high risk of chronic diseases such as diabetes, heart disease, and cancer, as well as the development of personalised treatment plans. It can also be used to find medications, identify disease subtypes, and forecast treatment outcomes.

Semi-Supervised Learning And Dementia Prevalence In Older Adults

A recent study used semi-supervised machine learning algorithms to analyse data from over 31,477 older adults and discovered that more than 60 million older adults in India aged 10 years and older may have dementia. The prevalence rate of dementia among older adults in India has been found to be 8.44 percent, which is lower than the prevalence rate for the same age group in the United States and the United Kingdom.

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