AIMC Topic: India

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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...

Comparative analysis of machine learning approaches for heatwave event prediction in India.

Scientific reports
Heatwaves, are identified as prolonged durations of unusually high temperatures, which pose significant threats to human health, animal health and agriculture. With the increasing frequency and intensity of heatwaves driven by climate change, accurat...

Leveraging machine learning for monitoring afforestation in mining areas: evaluating Tata Steel's restoration efforts in Noamundi, India.

Environmental monitoring and assessment
Mining activities have long been associated with significant environmental impacts, including deforestation, habitat degradation, and biodiversity loss, necessitating targeted strategies like afforestation to mitigate ecological damage. Tata Steel's ...

Soil moisture mapping in Indian tropical islands with C-band SAR and artificial neural network models.

Environmental monitoring and assessment
This study aims at analyzing the patterns of soil moisture in the South Andaman district using an integrated approach that incorporates Sentinel-1A C-band synthetic aperture radar (SAR) data and other auxiliary data from Sentinel-2A and Landsat 8. A ...

Enhancing particulate matter prediction in Delhi: insights from statistical and machine learning models.

Environmental monitoring and assessment
This study advances our approach to modeling particulate matter levels-specifically, PM and PM-in Delhi's dynamic urban environment through an extensive evaluation of traditional time series models (ARIMAX, SARIMAX) and machine learning models (RF, S...

Phase recognition in manual Small-Incision cataract surgery with MS-TCN + + on the novel SICS-105 dataset.

Scientific reports
Manual Small-Incision Cataract Surgery (SICS) is a prevalent technique in low- and middle-income countries (LMICs) but understudied with respect to computer assisted surgery. This prospective cross-sectional study introduces the first SICS video data...

Detection of β-Thalassemia trait from a heterogeneous population with red cell indices and parameters.

Computers in biology and medicine
BACKGROUND: India is home to about 42 million people with β-thalassemia trait (βTT) necessitating screening of βTT to stop spread of the disease. Over the years, researchers developed discrimination formulae based on red blood cell (RBC) parameters t...

Sex classification accuracy through machine learning algorithms - morphometric variables of human ear and nose.

BMC research notes
OBJECTIVE: Sex determination is an important parameter for personal identification in forensic and medico-legal examinations. The study aims at predicting sex accuracy from different parameters of ear and nose by using a novel approach of Machine Lea...

A retrospective study using machine learning to develop predictive model to identify rotavirus-associated acute gastroenteritis in children.

PeerJ
BACKGROUND: Rotavirus is the leading cause of severe dehydrating diarrhea in children under 5 years worldwide. Timely diagnosis is critical, but access to confirmatory testing is limited in hospital settings. Machine learning (ML) models have shown p...