SAARTHI : Real-Time Monitoring of Patients by Wearable Device

Priya, R. L.; Vaidya, Anish; Thorat, M.M.; Motwani, Vinit; Shinde, Chetas

doi:10.1109/accthpa49271.2020.9213239

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Cognitive Analytics‐Based Diagnostic Solutions in Healthcare Infrastructure

Ramakrishnan,

Murugesh,

Pulari

et al. 2024

Cognitive Analytics and Reinforcement Learning

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Cognitive Analytics‐Based Diagnostic Solutions in Healthcare Infrastructure

Ramakrishnan,

Murugesh,

Pulari

et al. 2024

Cognitive Analytics and Reinforcement Learning

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Internet of medical things‐based multitiered and hybrid architectural framework for effective heart disease prediction model

Priya

Jinny

2022

Concurrency and Computation

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Cardiovascular and chronic respiratory diseases are becoming a global threat. The alarming fact about Cardio-vascular diseases (CVD) is that rural areas are recording a high number of heart failures compared to urban areas. The proposed research work intends to create an effective medical setup in country-wide through Internet of Medical Things (IoMT)-based multitiered and hybrid architectural framework and Machine Learning (ML) model. The proposed architecture collects the medical data using the IoMT devices. During data preprocessing, categorical data are encoded using one-hot mechanism and is normalized using standard scalar technique. In addition, featureselection mechanisms are applied to choose the best significant features using hybrid sequence of Filter-Wrapper-Ensemble approach. To reduce the diagnostic barriers in health prediction model, an efficient method of Bayesian optimization for hyperparameter tuning and k-fold cross-validation resampling technique is applied to evaluate various conventional and ensemble ML techniques. The prediction results show the high accuracy of 86.47% and 85.81% using Logistic Regression and Extreme Gradient Boosting (XGBoosting) algorithm, respectively. In particular, the accuracy obtained using decision tree for the proposed approach is higher (80.53%) than that of existing approach (73.22%).

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A non-blind Watermarking Technique using Flexible Scaling Factor in Wavelet Transform

Elbaşi

2022

2022 45th International Conference on Telecommunications and Signal Processing (TSP)

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SAARTHI : Real-Time Monitoring of Patients by Wearable Device

Cited by 3 publications

References 0 publications

Cognitive Analytics‐Based Diagnostic Solutions in Healthcare Infrastructure

Cognitive Analytics‐Based Diagnostic Solutions in Healthcare Infrastructure

Internet of medical things‐based multitiered and hybrid architectural framework for effective heart disease prediction model

A non-blind Watermarking Technique using Flexible Scaling Factor in Wavelet Transform

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