Swapnali Kulkarni1 , Pravin Kumawat2 , Dipesh Nikam3 , Manisha Mali4

A comprehensive review of recent challenges faced by schizophrenic patients and how machine learning can be applied to overcome these challenges is being reviewed in this paper. In this paper, we explore various ML methodologies and techniques that contribute to development of personalized care and treatment systems. Showing adverse effects on behavioral patterns of an individual, such as disorganized speech and delusions, Schizophrenia is a critical disorder. Schizophrenic persons' may feel like they have lost touch with reality, bothering their family and friends. Symptoms for schizophrenia vary from person to person, however, three common categories are: psychotic, negative, and cognitive. Recognizing symptoms and seeking help at the earliest is very important in the case of this disorder. While there's no cure for schizophrenia, the study is leading to innovative and safer treatments. The current methods are not effective as the disease takes an average of 10 years to become diagnosed. To address this need, ML (machine learning) techniques are applied. The purpose of this study is to summarize data on the use of ML techniques in the prediction of schizophrenia, thereby aiding in the earliest and timeliest diagnosis of the disorder.

https://doi.org/10.58357/jedcs.2024.v3.i2.6