Menopause

Semantic prioritization in visual counterfactual explanations with weighted segmentation and auto-adaptive region selection.

In the domain of non-generative visual counterfactual explanations (CE), traditional techniques frequently involve the substitution of sections within a query image with corresponding sections from distractor images. Such methods have historically overlooked the semantic relevance of the replacement regions to the target object, thereby impairing the model's interpretability and hindering the edit...

Machine learning-based forecast of Helmet-CPAP therapy failure in Acute Respiratory Distress Syndrome patients.

BACKGROUND AND OBJECTIVE: Helmet-Continuous Positive Airway Pressure (H-CPAP) is a non-invasive respiratory support that is used for the treatment of Acute Respiratory Distress Syndrome (ARDS), a severe medical condition diagnosed when symptoms like profound hypoxemia, pulmonary opacities on radiography, or unexplained respiratory failure are present. It can be classified as mild, moderate or seve...

Machine learning algorithms in constructing prediction models for assisted reproductive technology (ART) related live birth outcomes.

Currently applicable models for predicting live birth outcomes in patients who received assisted reproductive technology (ART) have methodological or ...

Generation of deep learning based virtual non-contrast CT using dual-layer dual-energy CT and its application to planning CT for radiotherapy.

This paper presents a novel approach for generating virtual non-contrast planning computed tomography (VNC-pCT) images from contrast-enhanced planning...

Machine learning-based prediction of non-aeration linear alkylbenzene sulfonate mineralization in an oxygenic microalgal-bacteria biofilm.

Microalgal-bacteria biofilm shows great potential in low-cost greywater treatment. Accurately predicting treated greywater quality is of great signifi...

Predicting lncRNA-protein interactions using a hybrid deep learning model with dinucleotide-codon fusion feature encoding.

Long non-coding RNAs (lncRNAs) play crucial roles in numerous biological processes and are involved in complex human diseases through interactions wit...

Computer model for gait assessments in Parkinson's patients using a fuzzy inference model and inertial sensors.

Patients with Parkinson's disease (PD) in the moderate and severe stages can present several walk alterations. They can show slow movements and diffic...

Applying machine learning-based multiple imputation methods to nonparametric multiple comparisons in longitudinal clinical studies.

Dependent samples, in which repeated measurements are made on the same subjects, eliminate potential differences among the subjects. In k-dependent sa...

XGBoost-based nomogram for predicting lymph node metastasis in endometrial carcinoma.

This study aims to construct and optimize risk prediction models for lymph node metastasis (LNM) in endometrial carcinoma (EC) patients, thus improvin...

DMOIT: denoised multi-omics integration approach based on transformer multi-head self-attention mechanism.

Multi-omics data integration has become increasingly crucial for a deeper understanding of the complexity of biological systems. However, effectively ...

Deep learning-driven multi-omics sequential diagnosis with Hybrid-OmniSeq: Unraveling breast cancer complexity.

BackgroundBreast cancer results from an uncontrolled growth of breast tissue. Many methods of diagnosis are using multi-omics data to better understan...

Diagnostic accuracy of deep learning in prediction of osteoporosis: a systematic review and meta-analysis.

BACKGROUND: Osteoporosis is one of the most common metabolic diseases that is characterized by a decrease in bone density and a loss of the quality of...

Metabolomics-Based Machine Learning Models Accurately Predict Breast Cancer Estrogen Receptor Status.

Breast cancer is a global concern as a leading cause of death for women. Early and precise diagnosis can be vital in handling the disease efficiently....

The Effects of Perfluorooctanesulfonic acid (PFOS) on Human Umbilical Vein Endothelial Cells (HUVECs) Proliferation and Gene Expression and its Implications on Fetal Development.

Polyfluoro-alkyl substances (PFAS) are widely distributed environmental contaminants linked to human toxicity and developmental delays, especially low...

A Machine Learning-Based Prediction Model for the Probability of Fall Risk Among Chinese Community-Dwelling Older Adults.

Fall is a common adverse event among older adults. This study aimed to identify essential fall factors and develop a machine learning-based prediction...

Three-Dimensional Thermal Tomography with Physics-Informed Neural Networks.

: Accurate reconstruction of internal temperature fields from surface temperature data is critical for applications such as non-invasive thermal imagi...

Development and Validation of a Machine Learning Radiomics Model based on Multiparametric MRI for Predicting Progesterone Receptor Expression in Meningioma: A Multicenter Study.

RATIONALE AND OBJECTIVES: This study aimed to develop and validate a machine learning-based prediction model for preoperatively predicting progesteron...

A Novel Real-time Phase Prediction Network in EEG Rhythm.

Closed-loop neuromodulation, especially using the phase of the electroencephalography (EEG) rhythm to assess the real-time brain state and optimize th...

Bonevoyage: Navigating the depths of osteoporosis detection with a dual-core ensemble of cascaded ShuffleNet and neural networks.

BACKGROUND: Osteoporosis (OP) is a condition that significantly decreases bone density and strength, often remaining undetected until the occurrence o...

The Pivotal Role of Baseline LDCT for Lung Cancer Screening in the Era of Artificial Intelligence.

In this narrative review, we address the ongoing challenges of lung cancer (LC) screening using chest low-dose computerized tomography (LDCT) and expl...