[PDF][PDF] Heart Disease Classification for Early Diagnosis based on Adaptive Hoeffding Tree Algorithm in IoMT Data.

E Elbasi, AI Zreikat - Int. Arab J. Inf. Technol., 2023 - researchgate.net
Heart disease is a rapidly increasing disease that causes death worldwide. Therefore,
scientists around the globe start studying this issue from a different perspective to assure …

LA-ESN: a novel method for time series classification

H Sheng, M Liu, J Hu, P Li, Y Peng, Y Yi - Information, 2023 - mdpi.com
Time-series data is an appealing study topic in data mining and has a broad range of
applications. Many approaches have been employed to handle time series classification …

VMD and self-attention mechanism-based Bi-LSTM model for fault detection of optical fiber composite submarine cables

J Lu, W Feng, Y Li, J Zhang, Y Zou, J Li - EURASIP Journal on Advances in …, 2023 - Springer
As the main electrical equipment of offshore power grids, optical fiber composite submarine
cables undertake the task of power transmission and data communication. In order to ensure …

A lightweight pose sensing scheme for contactless abnormal gait behavior measurement

Y Zhao, J Li, X Wang, F Liu, P Shan, L Li, Q Fu - Sensors, 2022 - mdpi.com
The recognition of abnormal gait behavior is important in the field of motion assessment and
disease diagnosis. Currently, abnormal gait behavior is primarily recognized by pressure …

K Value Effect on Accuracy Using the K-NN for Heart Failure Dataset

A Masitha, MK Biddinika… - MATRIK: Jurnal …, 2023 - journal.universitasbumigora.ac.id
Heart failure is included in the category of cardiovascular disease. Heart disease is not easy
to detect, and its detection needs to be done by experienced and skilled medical …

Preparing Dual Data Normalization for KNN Classfication in Prediction of Heart Failure

A Masitha, MK Biddinika - KLIK: Kajian Ilmiah Informatika dan …, 2023 - djournals.com
Heart failure disease is a serious condition that is significant in affecting both a person's
quality of life and health. Therefore, it is important to develop classification methods that can …

Modelling virtual sensors for indoor environments with machine learning

DM Polanski, CM Angelopoulos - 2022 18th International …, 2022 - ieeexplore.ieee.org
Virtual Sensors model the sensing operation of physical sensors deployed in an area of
interest by generating sensory data with accuracy and precision close to those collected by …

Machine Learning for Myocardial Infarction Prediction Using Radial Basis Function and Genetic Algorithms

SR PM, A Nandhakumar… - … on Intelligent Cyber …, 2024 - ieeexplore.ieee.org
Cardiovascular disorders account for the primary cause of mortality for 32% of global deaths,
diagnosing them is a vital undertaking. Personalized medicine is being introduced in …

[PDF][PDF] Leveraging Natural language Processing and Machine Learning Techniques to find Frailty Deficits from Clinical Dataset

M Bazrafkan - 2023 - era.library.ualberta.ca
Introduction Frailty is a syndrome that is often associated with aging. It can be identified
through specific frailty scales or a comprehensive assessment by a healthcare provider. In …