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Heart Rate and its Variability From Short-Term ECG Recordings as Potential Biomarkers for Detecting Mild Cognitive Impairment.

American journal of Alzheimer's disease and other dementias
Alterations in Heart Rate (HR) and Heart Rate Variability (HRV) reflect autonomic dysfunction associated with neurodegeneration making them biomarkers suitable for detecting Mild Cognitive Impairment (MCI). The study involves 297 urban Indian parti...

Fuzzy APPSS: A novel method for quantifying COVID-19 impact in India under triangular spherical fuzzy environment.

Scientific reports
In the current scenario, decision-making models are essential for analyzing real-world problems. To address the dynamic nature of these problems, fuzzy decision-making models have been proposed by various researchers. However, an advanced technique i...

Integrating machine learning and remote sensing for long-term monitoring of chlorophyll-a in Chilika Lagoon, India.

Environmental monitoring and assessment
Chlorophyll-a (Chla) is recognized as a key indicator of water quality and ecological health in aquatic ecosystems, offering valuable insights into ecosystem dynamics and changes over time. This study aimed to to develop and validate a robust ML mode...

Soil temperature estimation at different depths using machine learning paradigms based on meteorological data.

Environmental monitoring and assessment
Knowledge of soil temperature (ST) is important for analysing environmental conditions and climate change. Moreover, ST is a vital element of soil that impacts crop growth as well as the germination of the seeds. In this study, four machine-learning ...

Can knowledge-based planning models validated on ethnically diverse patients lead to global standardisation of external beam radiation therapy for locally advanced cervix cancer?

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Knowledge-based planning (KBP) can consistently and efficiently create high-quality Volumetric Arc Therapy (VMAT) plans for cervix cancer. This study describes the cross-validation of two KBP models on geographically distinct ...

Use of Machine Learning to Predict Individual Postprandial Glycemic Responses to Food Among Individuals With Type 2 Diabetes in India: Protocol for a Prospective Cohort Study.

JMIR research protocols
BACKGROUND: Type 2 diabetes (T2D) is a leading cause of premature morbidity and mortality globally and affects more than 100 million people in the world's most populous country, India. Nutrition is a critical and evidence-based component of effective...

Noninvasive Anemia Detection and Hemoglobin Estimation from Retinal Images Using Deep Learning: A Scalable Solution for Resource-Limited Settings.

Translational vision science & technology
PURPOSE: The purpose of this study was to develop and validate a deep-learning model for noninvasive anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.

Time series forecasting of bed occupancy in mental health facilities in India using machine learning.

Scientific reports
Machine learning models are vital for forecasting and optimizing healthcare parameters, especially in the context of rising mental health issues in India and globally. With increasing demand for mental health services, effective resource management, ...

An examination of daily CO emissions prediction through a comparative analysis of machine learning, deep learning, and statistical models.

Environmental science and pollution research international
Human-induced global warming, primarily attributed to the rise in atmospheric CO, poses a substantial risk to the survival of humanity. While most research focuses on predicting annual CO emissions, which are crucial for setting long-term emission mi...

Incorporating computer vision on smart phone photographs into screening for inflammatory arthritis: results from an Indian patient cohort.

Rheumatology (Oxford, England)
OBJECTIVES: Convolutional neural networks (CNNs) are increasingly used to classify medical images, but few studies utilize smartphone photographs. The objective of this study was to assess CNNs for differentiating patients from controls and detecting...