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Scientists from Nanyang Technological University Singapore (NTU Singapore) have discovered that artificial intelligence (AI) has the potential to locate biomarkers of mental illnesses hidden among complex profiles of genetic markers and behavioral cues due to its efficiency in processing and deriving information from large datasets. .

The use of technology may also be able to predict whether a patient’s mental disability will worsen over time and assist in the development of individualized treatment plans that are specific to each patient’s needs.

One of the focus areas of NTU Singapore’s new Center for Biomedical Informatics is using the capabilities of AI and data science to aid in the prediction of mental health disorders.

The New Zealand-Singapore Data Science Research Program, a partnership between NTU Singapore, Institute of Mental Health (IMH) Singapore and Auckland University of Technology (AUT), is one of the initiatives which the center is working on to help predict schizophrenia in young people. The program creates machine learning computer models that identify biomarkers linked to the emergence of symptoms of schizophrenia.

Scientists want to determine how these factors relate to each other by combining all of this information into a single model. According to Assistant Professor Wilson Goh of NTU Singapore, correlations between gene expression and metabolic data have been identified through AI programs that analyze massive data sets. Physicians may be able to spot early signs of schizophrenia and treat the illness before the patient’s quality of life deteriorates by taking a closer look at additional dimensions of data.

Unlike schizophrenia, dementia is a brain disorder that primarily affects older people. Patients with advanced dementia suffer from memory loss, impaired judgment and confusion, which makes daily tasks more difficult.

NTU Singapore’s Dementia Research Center (Singapore) is creating AI-based solutions to detect and delay disease progression to address rising cases of dementia in aging populations in Asia and the rest of the world. the world.

One of the center’s projects is the Biomarkers and Cognitive Impairment Study (BioCIS), a five-year study aimed at understanding what happens to the brain in the early stages of dementia. It works with local hospitals to recruit 1,500 patients of all ethnicities who have mild cognitive impairment, the earliest stage of dementia.

By analyzing the structural attributes of the brain from brain scans, assessing brain activity with functional magnetic resonance imaging, and looking for protein biomarkers in the blood, BioCIS aims to find biomarkers linked to cognitive disorders.

Additionally, a non-invasive AI tool that can aid in the early detection of depression, a common mood condition that can strike at any age, has also been developed by NTU Singapore. Depression, which can be triggered by distressing life events, affects millions of people. People with depression typically experience mood swings that cause them to withdraw from society, and more than half of cases go undiagnosed and untreated.

The NTU Singapore team has created AI software that analyzes data from fitness trackers to find digital biomarkers of depression and predict a person’s risk of developing it. This technology is benefiting from the growing acceptance of wearable activity trackers.

The data allowed researchers to link specific patterns in participants’ fitness-tracking behaviors to depressive symptoms such as helplessness and hopelessness, loss of interest in routine tasks, and changes in mood. food or weight.

The computer could successfully identify people at high risk for depression and those without risk for depression with 80% accuracy in tests using data from depressed and healthy participants.

To help individuals, researchers, mental health professionals, and policy makers improve mental well-being, researchers believe Ycogni could be combined with Smart Buildings or Smart Cities efforts.