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Author

P. Deepthi

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Conference Aug 2026

An Innovation of Machine Learning in Mental Health: Predicting Mood in Real-Time using Bio signals from Wearable Devices and Patterns of Mobile Phone Use

Globally, mental health issues are on the rise, and mood assessment approaches rely on episodic self-reports and rare clinician tests. Traditional methods often miss everyday mood swings. A unique machine learning framework that integrates continuous biosignal data from wearable devices with passive behavioral cues fro...

A. Rani, M. Odeh, V. Pandi et al. · 0 citations
Conference Jul 2026

Artificial Intelligence for Spatial and Temporal Analysis of Climate Risks

The dynamic patterns of environmental risks discussed in the emergent analytical paradigm of this paper are the collective modelling of the spatial heterogeneity, the dynamic dynamics, and the uncertainty at the decision level of an adaptive architecture. The proposed method, called Adaptive Geo-Temporal Risk Intellige...

st Dilraj, Preet Kaur, B. Jain et al. · 0 citations
Conference Jun 2026

Data-Driven Climate Risk Forecasting Using Hybrid Machine Learning Models

This research proposes a new framework of analysis in predicting high-impact deviations in an environmental system in changing observational circumstances. The new approach, which is called Distribution-adaptive Uncertainty Synthesis (DAUS) is made to work without explicit physical assumptions or time-order-dependence,...

Dharavath Nagesh, P. Deepthi, A. Sahu et al. · 0 citations

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