AIMC Topic: India

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Machine learning-based ensemble of Global climate models and trend analysis for projecting extreme precipitation indices under future climate scenarios.

Environmental monitoring and assessment
Monitoring changes in climatic extremes is vital, as they influence current and future climate while significantly impacting ecosystems and society. This study examines trends in extreme precipitation indices over an Indian tropical river basin, anal...

Influence of sample size and machine learning algorithms on digital soil nutrient mapping accuracy.

Environmental monitoring and assessment
The objective of this study is to evaluate and compare the performance of different machine learning (ML) algorithms, viz., multi-layer perceptron (MLP), random forest (RF), extra trees regressor (ETR), CatBoost, and gradient boost (GB), considering ...

Optimizing treatment for depression in primary care using psychotherapy versus antidepressant medication in a low-resource setting: protocol for the OptimizeD randomized controlled trial.

BMC psychiatry
BACKGROUND: Psychotherapy and antidepressant medications are first-line treatments for depression, and they both have significant treatment effects on average. However, treatment response varies widely across patients, and neither approach is univers...

Optimizing potato yield predictions in Uttar Pradesh, India: a comparative analysis of machine learning models.

Scientific reports
Potato as a staple food, plays a crucial role in ensuring a sustainable food supply and mitigating poverty and malnutrition in various regions across the globe. India, specifically holding the second position in global potato production, plays a sign...

Menstrual Health Education Using a Specialized Large Language Model in India: Development and Evaluation Study of MenstLLaMA.

Journal of medical Internet research
BACKGROUND: The quality and accessibility of menstrual health education (MHE) in low- and middle-income countries, including India, remain inadequate due to persistent challenges (eg, poverty, social stigma, and gender inequality). While community-dr...

Mapping burnt areas using very high-resolution imagery and deep learning algorithms - a case study in Bandipur, India.

PloS one
Burnt area (BA) mapping is crucial for assessing wildfire impact, guiding restoration efforts, and improving fire management strategies. Accurate BA data helps estimate carbon emissions, biodiversity loss, and land surface properties post-fire change...

GeoAI-based soil erosion risk assessment in the Brahmaputra River Basin: a synergistic approach using RUSLE and advanced machine learning.

Environmental monitoring and assessment
Soil erosion is a critical environmental issue in the Brahmaputra River Basin, threatening agricultural productivity, water resources, and ecological balance. This study employs the revised universal soil loss equation (RUSLE) alongside remote sensin...

MIDAS: a technology-enabled hub-and-spoke system for the collection and dissemination of high-quality medical datasets in India.

BMC medical informatics and decision making
BACKGROUND: The need for better AI models fuels the demand for larger and larger high-quality datasets with significant diversity. Over the years, many medical imaging datasets have been published globally, but existing datasets do not contain enough...

Analyzing mental stress in Indian students through advanced machine learning and wearable technologies.

Scientific reports
Mental stress is a prevalent issue in modern society, and detecting and classifying it accurately is crucial for effective interventions and treatment plans. This study aims to compare various machine learning (ML) algorithms for detecting mental str...

Evaluation of different spectral indices for wheat lodging assessment using machine learning algorithms.

Scientific reports
Wheat lodging is a recurrent phenomenon that significantly affects grain yield and impedes the harvesting efficiency. Therefore, the precise and rapid assessment of wheat lodging is crucial in minimizing its impact on grain yield and quality. Recentl...