01/04/2026
𝐁𝐚𝐭𝐜𝐡-𝟕 (𝐌𝐑𝐈)
🔓 A total of 5 author positions are currently available.
𝐒𝐡𝐨𝐫𝐭 𝐓𝐢𝐭𝐥𝐞: 𝙎𝙘𝙤𝙥𝙪𝙨 𝙌1: 𝙀𝙭𝙥𝙡𝙖𝙞𝙣𝙖𝙗𝙡𝙚 𝙈𝙖𝙘𝙝𝙞𝙣𝙚 𝙇𝙚𝙖𝙧𝙣𝙞𝙣𝙜 𝙛𝙤𝙧 𝘿𝙚𝙥𝙧𝙚𝙨𝙨𝙞𝙤𝙣 𝙖𝙣𝙙 𝘼𝙣𝙭𝙞𝙚𝙩𝙮 𝙍𝙞𝙨𝙠 𝙎𝙩𝙧𝙖𝙩𝙞𝙛𝙞𝙘𝙖𝙩𝙞𝙤𝙣
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Short Details: [Abstract]
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Background:
Depression and anxiety are two of the leading contributors to the global burden of mental disorders. However, existing risk stratification approaches are based on few clinical markers and are not easily
interpretable for preventive interventions. The integration of lifestyle factors, psychosocial stressors, and behavioral health indicators with explainable machine learning is a potential approach for risk identification and discovering modifiable risk factors for targeted interventions.
Objective:
The aims of this study were to develop an explainable machine learning model to predict depression and anxiety risk using multidimensional lifestyle and psychosocial stressor profiles, and to determine interpretable phenotypic clusters with modifiable intervention pathways.
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Q1-Level Research Project (Under Professor’s Supervision)
We are initiating a Q1-level advanced research project involving 7 authors. The project will be supervised by a professor, who will conduct 4–5 high-level research sessions, each approximately 4 hours long.
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Research Project is starting on 𝐀𝐩𝐫𝐢𝐥 𝟏𝟕, 𝟐𝟎𝟐𝟔. Learn and conduct high-quality research under the supervision of a professor!
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During this program, participants will:
* Learn and practice hands-on research training,
* Work on a real research project,
* And prepare the research for journal publication under the professor’s direct guidance.
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👤 1st Author: 1/1 (Mr Jamal)
👤 2nd Author: 0/1
👤 3rd Author: 0/1
👤 4th Author: 0/1
👤 5th Author: 0/1
👤 6th Author: 1/1 (Ms. Shamim)
👤 7th Author: 0/1
🔓 A total of 5 author positions are currently available
