Application of artificial intelligence methods in vital signs analysis of hospitalized patients: A systematic literature review

N Kaieski, CA Da Costa, R da Rosa Righi, PS Lora… - Applied Soft …, 2020 - Elsevier
In a hospital environment, patients are monitored continuously by electronic devices and
health professionals. Therefore, a large amount of data is collected and stored in electronic …

A service-based joint model used for distributed learning: Application for smart agriculture

D Vimalajeewa, C Kulatunga, DP Berry… - … on Emerging Topics …, 2021 - ieeexplore.ieee.org
Distributed analytics facilitate to make the data-driven services smarter for a wider range of
applications in many domains, including agriculture. The key to producing services at such …

[HTML][HTML] Machine learning for predicting pathological complete response in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy

CM Huang, MY Huang, CW Huang, HL Tsai, WC Su… - Scientific reports, 2020 - nature.com
For patients with locally advanced rectal cancer (LARC), achieving a pathological complete
response (pCR) after neoadjuvant chemoradiotherapy (CRT) provides them with the optimal …

机器学习在疾病预测的应用研究进展

刘雨安, 杨小文, 李乐之 - 护理学报, 2021 - manu68.magtech.com.cn
!"#$%&'()*+,-./0 Page 1 2021 年4 月 护理学报 April,2021 第28 卷第7 期Journal of Nursing(China)
Vol.28 No.7 [26] Cartwright J, Franklin D, Forman D, et al. Promoting Colr laborative …

Performance Evaluation of Machine Learning‐Based Channel Equalization Techniques: New Trends and Challenges

S Hassan, N Tariq, RA Naqvi, AU Rehman… - Journal of …, 2022 - Wiley Online Library
Wireless communication systems have evolved and offered more smart and advanced
systems like ad hoc and sensor‐based infrastructure fewer networks. These networks are …

Automatic label‐free detection of breast cancer using nonlinear multimodal imaging and the convolutional neural network ResNet50

N Ali, E Quansah, K Köhler, T Meyer… - Translational …, 2019 - Wiley Online Library
Breast cancer is the main cause of all female cancer deaths worldwide. Because of the lack
of early symptoms, the early detection of breast cancer becomes challenging. This detection …

Meniscal tear and ACL injury detection model based on AlexNet and iterative ReliefF

S Key, M Baygin, S Demir, S Dogan, T Tuncer - Journal of Digital Imaging, 2022 - Springer
Magnetic resonance (MR) is one of the special imaging techniques used to diagnose
orthopedics and traumatology. In this study, a new method has been proposed to detect …

An integration of blockchain and machine learning into the health care system

MS Arza, SK Panda - Machine Learning Adoption in Blockchain …, 2022 - taylorfrancis.com
Currently, machine learning and blockchain play a predominant role in the health care
sector. In health care, machine learning is most commonly used for administrative purposes …

Training and interpreting machine learning algorithms to evaluate fall risk after emergency department visits

BW Patterson, CJ Engstrom, V Sah, MA Smith… - Medical care, 2019 - journals.lww.com
Background: Machine learning is increasingly used for risk stratification in health care.
Achieving accurate predictive models do not improve outcomes if they cannot be translated …

[HTML][HTML] A Machine Learning-Based Method for Detecting Liver Fibrosis

M Suárez, R Martínez, AM Torres, A Ramón, P Blasco… - Diagnostics, 2023 - mdpi.com
Cholecystectomy and Metabolic-associated steatotic liver disease (MASLD) are prevalent
conditions in gastroenterology, frequently co-occurring in clinical practice. Cholecystectomy …