Ethics

Machine Learning-Driven D-Glucose Prediction Using a Novel Biosensor for Non-Invasive Diabetes Management.

Developing reliable noninvasive diagnostic and monitoring systems for diabetes remains a significant...

GALR1 and PENK serve as potential biomarkers in invasive non-functional pituitary neuroendocrine tumours.

BACKGROUND: Some nonfunctioning pituitary neuroendocrine tumor (NFPitNET) can show invasive growth, ...

Development and evaluation of USCnet: an AI-based model for preoperative prediction of infectious and non-infectious urolithiasis.

BACKGROUND: Urolithiasis, a prevalent condition characterized by a high rate of incidence and recurr...

Predicting oleogels properties using non-invasive spectroscopic techniques and machine learning.

Oleogelators are considered food additives that require approval from regulatory authorities. Theref...

Deep-learning tool for early identification of non-traumatic intracranial hemorrhage etiology and application in clinical diagnostics based on computed tomography (CT) scans.

BACKGROUND: To develop an artificial intelligence system that can accurately identify acute non-trau...

Non-invasive classification of non-neoplastic and neoplastic gallbladder polyps based on clinical imaging and ultrasound radiomics features: An interpretable machine learning model.

BACKGROUND: Gallbladder (GB) adenomas, precancerous lesions for gallbladder carcinoma (GBC), lack re...

Non-Invasive Biomarkers in the Era of Big Data and Machine Learning.

Invasive diagnostic techniques, while offering critical insights into disease pathophysiology, are o...

Continuous non-contact monitoring of neonatal activity.

PURPOSE: Neonatal activity is an important physiological parameter in the neonatal intensive care un...

Big data analysis and machine learning of the role of cuproptosis-related long non-coding RNAs (CuLncs) in the prognosis and immune landscape of ovarian cancer.

BACKGROUND: Ovarian cancer (OC) is a severe malignant tumor with a significant threat to women's hea...

[MP-MRI in the evaluation of non-operative treatment response, for residual and recurrent tumor detection in head and neck cancer].

As non-surgical therapies gain acceptance in head and neck tumors, the importance of imaging has inc...

Leveraging Radiomics and Hybrid Quantum-Classical Convolutional Networks for Non-Invasive Detection of Microsatellite Instability in Colorectal Cancer.

PURPOSE: The goal of this study is to create a novel framework for identifying MSI status in colorec...

Artificial Intelligence non-invasive methods for neonatal jaundice detection: A review.

Neonatal jaundice is a common and potentially fatal health condition in neonates, especially in low ...

A deep learning approach: physics-informed neural networks for solving a nonlinear telegraph equation with different boundary conditions.

The nonlinear Telegraph equation appears in a variety of engineering and science problems. This pape...

Deep learning-based time-of-flight (ToF) enhancement of non-ToF PET scans for different radiotracers.

AIM: To evaluate a deep learning-based time-of-flight (DLToF) model trained to enhance the image qua...

Machine learning classification of active viewing of pain and non-pain images using EEG does not exceed chance in external validation samples.

Previous research has demonstrated that machine learning (ML) could not effectively decode passive o...

Cooperative Magnetic Interfacial Microrobot Couple for Versatile Non-Contact Biomedical Applications.

Magnetic interfacial microrobots are increasingly recognized as a promising approach for potential b...

Sub-1-min relaxation-enhanced non-contrast non-triggered cervical MRA using compressed SENSE with deep learning reconstruction in healthy volunteers.

BACKGROUND: We evaluated the acceleration of a three-dimensional isotropic flow-independent magnetic...

Non-destructive origin and ginsenoside analysis of American ginseng via NIR and deep learning.

American ginseng is widely in demand as a famous medicinal herb, but the production conditions affec...

Label-efficient sequential model-based weakly supervised intracranial hemorrhage segmentation in low-data non-contrast CT imaging.

BACKGROUND: In clinical settings, intracranial hemorrhages (ICH) are routinely diagnosed using non-c...

Development and validation of MRI-derived deep learning score for non-invasive prediction of PD-L1 expression and prognostic stratification in head and neck squamous cell carcinoma.

BACKGROUND: Immunotherapy has revolutionized the treatment landscape for head and neck squamous cell...

Advancing tele-perception: a paradigm shift from traditional non-contact sensing to adaptive embodied artificial intelligence systems.