Demystifying supervised learning in healthcare 4.0: A new reality of transforming diagnostic medicine

S Roy, T Meena, SJ Lim - Diagnostics, 2022 - mdpi.com
The global healthcare sector continues to grow rapidly and is reflected as one of the fastest-
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …

Deep learning-based medical images segmentation of musculoskeletal anatomical structures: a survey of bottlenecks and strategies

L Bonaldi, A Pretto, C Pirri, F Uccheddu, CG Fontanella… - Bioengineering, 2023 - mdpi.com
By leveraging the recent development of artificial intelligence algorithms, several medical
sectors have benefited from using automatic segmentation tools from bioimaging to segment …

Combining the transformer and convolution for effective brain tumor classification using MRI images

M Aloraini, A Khan, S Aladhadh, S Habib… - Applied Sciences, 2023 - mdpi.com
In the world, brain tumor (BT) is considered the major cause of death related to cancer,
which requires early and accurate detection for patient survival. In the early detection of BT …

Technological advancements and elucidation gadgets for Healthcare applications: An exhaustive methodological review-part-I (AI, big data, block chain, open-source …

S Siripurapu, NK Darimireddy, A Chehri, B Sridhar… - Electronics, 2023 - mdpi.com
In the realm of the emergence and spread of infectious diseases with pandemic potential
throughout the history, plenty of pandemics (and epidemics), from the plague to AIDS (1981) …

A lightweight crop pest detection method based on convolutional neural networks

Z Cheng, R Huang, R Qian, W Dong, J Zhu, M Liu - Applied Sciences, 2022 - mdpi.com
Existing object detection methods with many parameters and computations are not suitable
for deployment on devices with poor performance in agricultural environments. Therefore …

Hybrid techniques of x-ray analysis to predict knee osteoarthritis grades based on fusion features of cnn and handcrafted

A Khalid, EM Senan, K Al-Wagih, MM Ali Al-Azzam… - Diagnostics, 2023 - mdpi.com
Knee osteoarthritis (KOA) is a chronic disease that impedes movement, especially in the
elderly, affecting more than 5% of people worldwide. KOA goes through many stages, from …

Anterior cruciate ligament tear detection based on deep belief networks and improved honey badger algorithm

J Sun, L Wang, N Razmjooy - Biomedical Signal Processing and Control, 2023 - Elsevier
Abstract The Anterior Cruciate Ligament (ACL) tear is a common injury among athletes who
participate in extreme sports such as basketball, football, American football, and skiing …

Automatic segmentation of lumbar spine MRI images based on improved attention U‐net

S Wang, Z Jiang, H Yang, X Li… - Computational …, 2022 - Wiley Online Library
Lumbar spine segmentation is important to help doctors diagnose lumbar disc herniation
(LDH) and patients' rehabilitation treatment. In order to accurately segment the lumbar spine …

[Retracted] Machine Learning‐Based Performance Comparison to Diagnose Anterior Cruciate Ligament Tears

MJ Awan, MS Mohd Rahim, N Salim… - Journal of …, 2022 - Wiley Online Library
In recent times, knee joint pains have become severe enough to make daily tasks difficult.
Knee osteoarthritis is a type of arthritis and a leading cause of disability worldwide. The …

MGACA-Net: A novel deep learning based multi-scale guided attention and context aggregation for localization of knee anterior cruciate ligament tears region in MRI …

MJ Awan, MSM Rahim, N Salim, H Nobanee… - PeerJ Computer …, 2023 - peerj.com
Anterior cruciate ligament (ACL) tears are a common knee injury that can have serious
consequences and require medical intervention. Magnetic resonance imaging (MRI) is the …