AIMC Topic: Humans

Clear Filters Showing 38041 to 38050 of 95995 articles

Evaluation of thin-slice abdominal DECT using deep-learning image reconstruction in 74 keV virtual monoenergetic images: an image quality comparison.

Abdominal radiology (New York)
PURPOSE: To compare noise, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR) and image quality using deep-learning image reconstruction (DLIR) vs. adaptive statistical iterative reconstruction (ASIR-V) in 0.625 and 2.5 mm slice thickness gra...

A Machine Learning-Combined Flexible Sensor for Tactile Detection and Voice Recognition.

ACS applied materials & interfaces
Intelligent sensors have attracted substantial attention for various applications, including wearable electronics, artificial intelligence, healthcare monitoring, and human-machine interactions. However, there still remains a critical challenge in de...

Clinical applications of deep learning in breast MRI.

Biochimica et biophysica acta. Reviews on cancer
Deep learning (DL) is one of the most powerful data-driven machine-learning techniques in artificial intelligence (AI). It can automatically learn from raw data without manual feature selection. DL models have led to remarkable advances in data extra...

Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach.

EBioMedicine
BACKGROUND: Since the US reported its first COVID-19 case on January 21, 2020, the science community has been applying various techniques to forecast incident cases and deaths. To date, providing an accurate and robust forecast at a high spatial reso...

Brain Tumor Segmentation and Classification from Sensor-Based Portable Microwave Brain Imaging System Using Lightweight Deep Learning Models.

Biosensors
Automated brain tumor segmentation from reconstructed microwave (RMW) brain images and image classification is essential for the investigation and monitoring of the progression of brain disease. The manual detection, classification, and segmentation ...

Exploring a global interpretation mechanism for deep learning networks when predicting sepsis.

Scientific reports
The purpose of this study is to identify additional clinical features for sepsis detection through the use of a novel mechanism for interpreting black-box machine learning models trained and to provide a suitable evaluation for the mechanism. We use ...

Combining robot-assisted therapy with virtual reality or using it alone? A systematic review on health-related quality of life in neurological patients.

Health and quality of life outcomes
BACKGROUND: In the field of neurorehabilitation, robot-assisted therapy (RAT) and virtual reality (VR) have so far shown promising evidence on multiple motor and functional outcomes. The related effectiveness on patients' health-related quality of li...

Uncovering psychiatric phenotypes using unsupervised machine learning: A data-driven symptoms approach.

European psychiatry : the journal of the Association of European Psychiatrists
BACKGROUND: Current categorical classification systems of psychiatric diagnoses lead to heterogeneity of symptoms within disorders and common co-occurrence of disorders. We investigated the heterogeneous and overlapping nature of symptom endorsement ...

Non-destructive classification of unlabeled cells: Combining an automated benchtop magnetic resonance scanner and artificial intelligence.

PLoS computational biology
In order to treat degenerative diseases, the importance of advanced therapy medicinal products has increased in recent years. The newly developed treatment strategies require a rethinking of the appropriate analytical methods. Current standards are m...