AIMC Topic: Humans

Clear Filters Showing 47971 to 47980 of 95995 articles

The new SUMPOT to predict postoperative complications using an Artificial Neural Network.

Scientific reports
An accurate assessment of preoperative risk may improve use of hospital resources and reduce morbidity and mortality in high-risk surgical patients. This study aims at implementing an automated surgical risk calculator based on Artificial Neural Netw...

Clinical application of robotic orthopedic surgery: a bibliometric study.

BMC musculoskeletal disorders
OBJECTIVES: The present study aimed to evaluate the status and trends of robotic orthopedic surgery in a clinical setting using bibliometrics.

Comparison of RetinaNet, SSD, and YOLO v3 for real-time pill identification.

BMC medical informatics and decision making
BACKGROUND: The correct identification of pills is very important to ensure the safe administration of drugs to patients. Here, we use three current mainstream object detection models, namely RetinaNet, Single Shot Multi-Box Detector (SSD), and You O...

Improving random forest predictions in small datasets from two-phase sampling designs.

BMC medical informatics and decision making
BACKGROUND: While random forests are one of the most successful machine learning methods, it is necessary to optimize their performance for use with datasets resulting from a two-phase sampling design with a small number of cases-a common situation i...

UMLF-COVID: an unsupervised meta-learning model specifically designed to identify X-ray images of COVID-19 patients.

BMC medical imaging
BACKGROUND: With the rapid spread of COVID-19 worldwide, quick screening for possible COVID-19 patients has become the focus of international researchers. Recently, many deep learning-based Computed Tomography (CT) image/X-ray image fast screening mo...

Improving the Classification Performance of Esophageal Disease on Small Dataset by Semi-supervised Efficient Contrastive Learning.

Journal of medical systems
The classification of esophageal disease based on gastroscopic images is important in the clinical treatment, and is also helpful in providing patients with follow-up treatment plans and preventing lesion deterioration. In recent years, deep learning...

Intelligent Monitoring of Care Status for COPD Patients Based on Deep Learning.

Contrast media & molecular imaging
To discuss the application method and effect of COPD patients in deep learning in intelligent monitoring, two groups were used under a reasonable selection of antibiotics specifically including reasonable and effective oxygen administration, atomizat...

Tool for Predicting, Scanning, and Designing Defensins.

Frontiers in immunology
Defensins are host defense peptides present in nearly all living species, which play a crucial role in innate immunity. These peptides provide protection to the host, either by killing microbes directly or indirectly by activating the immune system. ...

Deep Learning-Based Detection and Diagnosis of Subarachnoid Hemorrhage.

Journal of healthcare engineering
Subarachnoid hemorrhage (SAH) is one of the critical and severe neurological diseases with high morbidity and mortality. Head computed tomography (CT) is among the preferred methods for the diagnosis of SAH, which is confirmed by CT showing high-dens...

FWNNet: Presentation of a New Classifier of Brain Tumor Diagnosis Based on Fuzzy Logic and the Wavelet-Based Neural Network Using Machine-Learning Methods.

Computational intelligence and neuroscience
In this paper, we present a novel classifier based on fuzzy logic and wavelet transformation in the form of a neural network. This classifier includes a layer to predict the numerical feature corresponded to labels or classes. The presented classifie...