AIMC Topic: Humans

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SecProCT: In Silico Prediction of Human Secretory Proteins Based on Capsule Network and Transformer.

International journal of molecular sciences
Identifying secretory proteins from blood, saliva or other body fluids has become an effective method of diagnosing diseases. Existing secretory protein prediction methods are mainly based on conventional machine learning algorithms and are highly de...

X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic.

BioMed research international
PURPOSE: Due to the excessive use of raw materials in diagnostic tools and equipment during the COVID-19 pandemic, there is a dire need for cheaper and more effective methods in the healthcare system. With the development of artificial intelligence (...

Exoskeleton end-effector robot-assisted therapy for finger-hand motor recovery in stroke survivors: systematic review and meta-analysis.

Topics in stroke rehabilitation
INTRODUCTION: The growing number of stroke survivors with residual hand disabilities requires the development of efficient recovery therapy, and robotic rehabilitation can play an important role.

Retzius Sparing Radical Prostatectomy Versus Robot-assisted Radical Prostatectomy: Which Technique Is More Beneficial for Prostate Cancer Patients (MASTER Study)? A Systematic Review and Meta-analysis.

European urology focus
CONTEXT: Retzius sparing robot-assisted radical prostatectomy (RS-RARP) is increasingly being used, but results of pertinent studies on perioperative, functional, and oncological outcomes comparing the Retzius sparing approach with standard robot-ass...

Systematic Review of the Effectiveness of Machine Learning Algorithms for Classifying Pain Intensity, Phenotype or Treatment Outcomes Using Electroencephalogram Data.

The journal of pain
Recent attempts to utilize machine learning (ML) to predict pain-related outcomes from Electroencephalogram (EEG) data demonstrate promising results. The primary aim of this review was to evaluate the effectiveness of ML algorithms for predicting pai...

Efficacy of a deep leaning model created with the transfer learning method in detecting sialoliths of the submandibular gland on panoramic radiography.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: This study aimed to compare the performance of 3 deep learning models, including a model constructed with the transfer learning method, in detecting submandibular gland sialoliths on panoramic radiographs.

Molecular subtyping of diffuse gliomas using magnetic resonance imaging: comparison and correlation between radiomics and deep learning.

European radiology
OBJECTIVES: The molecular subtyping of diffuse gliomas is important. The aim of this study was to establish predictive models based on preoperative multiparametric MRI.

Seeing under the cover with a 3D U-Net: point cloud-based weight estimation of covered patients.

International journal of computer assisted radiology and surgery
PURPOSE: Body weight is a crucial parameter for patient-specific treatments, particularly in the context of proper drug dosage. Contactless weight estimation from visual sensor data constitutes a promising approach to overcome challenges arising in e...

Deep learning for radial SMS myocardial perfusion reconstruction using the 3D residual booster U-net.

Magnetic resonance imaging
PURPOSE: To develop an end-to-end deep learning solution for quickly reconstructing radial simultaneous multi-slice (SMS) myocardial perfusion datasets with comparable quality to the pixel tracking spatiotemporal constrained reconstruction (PT-STCR) ...