Predictive analysis of heart diseases with machine learning approaches
Abstract Machine Learning (ML) is used in healthcare sectors worldwide. ML methods help
in the protection of heart diseases, locomotor disorders in the medical data set. The …
in the protection of heart diseases, locomotor disorders in the medical data set. The …
Hybrid model for detection of cervical cancer using causal analysis and machine learning techniques
Cervical cancer has become the third most common form of cancer in the in‐universe, after
the widespread breast cancer. Human papillomavirus risk of infection is linked to the …
the widespread breast cancer. Human papillomavirus risk of infection is linked to the …
Hybrid CNN-LSTM model with efficient hyperparameter tuning for prediction of Parkinson's disease
The patients' vocal Parkinson's disease (PD) changes could be identified early on, allowing
for management before physically incapacitating symptoms appear. In this work, static as …
for management before physically incapacitating symptoms appear. In this work, static as …
An early detection and segmentation of Brain Tumor using Deep Neural Network
Background Magnetic resonance image (MRI) brain tumor segmentation is crucial and
important in the medical field, which can help in diagnosis and prognosis, overall growth …
important in the medical field, which can help in diagnosis and prognosis, overall growth …
Automated brain tumor identification using magnetic resonance imaging: A systematic review and meta-analysis
O Kouli, A Hassane, D Badran, T Kouli… - Neuro-oncology …, 2022 - academic.oup.com
Background Automated brain tumor identification facilitates diagnosis and treatment
planning. We evaluate the performance of traditional machine learning (TML) and deep …
planning. We evaluate the performance of traditional machine learning (TML) and deep …
[HTML][HTML] Evaluation of IoT-Enabled hybrid model for genome sequence analysis of patients in healthcare 4.0
Genome sequence matching is vital for health analytics and treatment in healthcare 4.0. It
focuses on finding whether a given sequence resembles other sequences that can help …
focuses on finding whether a given sequence resembles other sequences that can help …
[HTML][HTML] Remote monitoring system using slow-fast deep convolution neural network model for identifying anti-social activities in surveillance applications
EM Onyema, S Balasubaramanian, C Iwendi… - Measurement …, 2023 - Elsevier
Remote monitoring is the process that monitors and observes information from a distance
utilizing sensors or electronic types of equipment. Remote monitoring is used in real-time …
utilizing sensors or electronic types of equipment. Remote monitoring is used in real-time …
Prevalence and risk factors analysis of postpartum depression at early stage using hybrid deep learning model
Abstract Postpartum Depression Disorder (PPDD) is a prevalent mental health condition and
results in severe depression and suicide attempts in the social community. Prompt actions …
results in severe depression and suicide attempts in the social community. Prompt actions …
Segmentation and Classification of Encephalon Tumor by Applying Improved Fast and Robust FCM Algorithm with PSO‐Based ELM Technique
Nowadays, so many people are living in world. If so many people are living, then the
diseases are also increasing day by day due to adulterated and chemical content food. The …
diseases are also increasing day by day due to adulterated and chemical content food. The …
Local-ternary-pattern-based associated histogram equalization technique for cervical cancer detection
Every year, cervical cancer is a leading cause of mortality in women all over the world. This
cancer can be cured if it is detected early and patients are treated promptly. This study …
cancer can be cured if it is detected early and patients are treated promptly. This study …