InfusedHeart: A novel knowledge-infused learning framework for diagnosis of cardiovascular events
S Pandya, TR Gadekallu, PK Reddy… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
In the undertaken study, we have used a customized dataset termed``Cardiac-200''and the
benchmark dataset``PhysioNet.''which contains 1500 heartbeat acoustic event samples …
benchmark dataset``PhysioNet.''which contains 1500 heartbeat acoustic event samples …
Deep learning-based transfer learning for classification of skin cancer
One of the major health concerns for human society is skin cancer. When the pigments
producing skin color turn carcinogenic, this disease gets contracted. A skin cancer diagnosis …
producing skin color turn carcinogenic, this disease gets contracted. A skin cancer diagnosis …
Deep learning can predict survival directly from histology in clear cell renal cell carcinoma
F Wessels, M Schmitt, E Krieghoff-Henning, JN Kather… - PLoS …, 2022 - journals.plos.org
For clear cell renal cell carcinoma (ccRCC) risk-dependent diagnostic and therapeutic
algorithms are routinely implemented in clinical practice. Artificial intelligence-based image …
algorithms are routinely implemented in clinical practice. Artificial intelligence-based image …
Early detection of cardiorespiratory complications and training monitoring using wearable ECG sensors and CNN
HY Lu, XM Feng, J Zhang - BMC Medical Informatics and Decision Making, 2024 - Springer
This research study demonstrates an efficient scheme for early detection of cardiorespiratory
complications in pandemics by Utilizing Wearable Electrocardiogram (ECG) sensors for …
complications in pandemics by Utilizing Wearable Electrocardiogram (ECG) sensors for …
Machine learning predicts translation initiation sites in neurologic diseases with nucleotide repeat expansions
A number of neurologic diseases associated with expanded nucleotide repeats, including
an inherited form of amyotrophic lateral sclerosis, have an unconventional form of translation …
an inherited form of amyotrophic lateral sclerosis, have an unconventional form of translation …
An effective up-sampling approach for breast cancer prediction with imbalanced data: A machine learning model-based comparative analysis
Early detection of breast cancer plays a critical role in successful treatment that saves
thousands of lives of patients every year. Despite massive clinical data have been collected …
thousands of lives of patients every year. Despite massive clinical data have been collected …
[PDF][PDF] The application of machine learning to the prediction of heart attack.
Heart illnesses are among the most significant contributors to mortality in the world in the
modern era. Heart attacks are responsible for the death of one person every 33 seconds …
modern era. Heart attacks are responsible for the death of one person every 33 seconds …
Artificial intelligence-enabled electrocardiography predicts left ventricular dysfunction and future cardiovascular outcomes: a retrospective analysis
BACKGROUND: The ejection fraction (EF) provides critical information about heart failure
(HF) and its management. Electrocardiography (ECG) is a noninvasive screening tool for …
(HF) and its management. Electrocardiography (ECG) is a noninvasive screening tool for …
[HTML][HTML] Machine learning-based smart wearable system for cardiac arrest monitoring using hybrid computing
Every year, the percentage of people affected by cardiovascular diseases increases
drastically. Out of them, a heart attack is the most prominent and painful disease. According …
drastically. Out of them, a heart attack is the most prominent and painful disease. According …
A novel feature selection approach with integrated feature sensitivity and feature correlation for improved prediction of heart disease
This paper presents a random forest-feature sensitivity and feature correlation (RF-FSFC)
technique for enhanced heart disease prediction. The proposed methodology is …
technique for enhanced heart disease prediction. The proposed methodology is …