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Emergence of flexible technology in developing advanced systems for post-stroke rehabilitation: a comprehensive review.

Stroke is one of the most common neural disorders, which causes physical disabilities and motor impa...

An Explainable Machine Learning Model for Material Backorder Prediction in Inventory Management.

Global competition among businesses imposes a more effective and low-cost supply chain allowing firm...

Post-script-Retail forecasting: Research and practice.

This note updates the 2019 review article "Retail forecasting: Research and practice" in the context...

A Bidirectional Interpolation Method for Post-Processing in Sampling-Based Robot Path Planning.

This paper proposes a post-processing method called bidirectional interpolation method for sampling-...

Autonomous Thermal Vision Robotic System for Victims Recognition in Search and Rescue Missions.

Technological breakthroughs in recent years have led to a revolution in fields such as Machine Visio...

Robotic repair of post-oesophagectomy hiatal hernia.

Diaphragmatic hiatal hernia is a potential complication of oesophagectomy in cancer patients. Over t...

Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies.

Interstitial fibrosis, tubular atrophy, and inflammation are major contributors to kidney allograft ...

Robot-assisted stereoelectroencephalography in young children: technical challenges and considerations.

Robot-assisted stereoelectroencephalography (sEEG) is frequently employed to localize epileptogenic ...

A deep learning model for burn depth classification using ultrasound imaging.

Identification of burn depth with sufficient accuracy is a challenging problem. This paper presents ...

Deep learning-based thin-section MRI reconstruction improves tumour detection and delineation in pre- and post-treatment pituitary adenoma.

Even a tiny functioning pituitary adenoma could cause symptoms; hence, accurate diagnosis and treatm...

Quantifying the Impacts of Pre- and Post-Conception TSH Levels on Birth Outcomes: An Examination of Different Machine Learning Models.

BACKGROUND: While previous studies identified risk factors for diverse pregnancy outcomes, tradition...

Automated post-operative brain tumour segmentation: A deep learning model based on transfer learning from pre-operative images.

Automated brain tumour segmentation from post-operative images is a clinically relevant yet challeng...

The Route of Motor Recovery in Stroke Patients Driven by Exoskeleton-Robot-Assisted Therapy: A Path-Analysis.

: Exoskeleton-robot-assisted therapy is known to positively affect the recovery of arm functions in ...

Deceptive Online Content Detection Using Only Message Characteristics and a Machine Learning Trained Expert System.

This paper considers the use of a post metadata-based approach to identifying intentionally deceptiv...

Post-reconstruction attenuation correction for SPECT myocardium perfusion imaging facilitated by deep learning-based attenuation map generation.

BACKGROUND: Attenuation correction can improve the quantitative accuracy of single-photon emission c...

Non-transfer Deep Learning of Optical Coherence Tomography for Post-hoc Explanation of Macular Disease Classification.

Deep transfer learning is a popular choice for classifying monochromatic medical images using models...

Estimation of current and post-treatment retinal function in chronic central serous chorioretinopathy using artificial intelligence.

Refined understanding of the association of retinal microstructure with current and future (post-tre...

Prediction of post-stroke cognitive impairment using brain FDG PET: deep learning-based approach.

PURPOSE: Post-stroke cognitive impairment can affect up to one third of stroke survivors. Since cogn...

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