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Ultrafast T2-weighted MR imaging of the urinary bladder using deep learning-accelerated HASTE at 3 Tesla.

BMC medical imaging
OBJECTIVE: This prospective study aimed to assess the feasibility of a half-Fourier single-shot turbo spin echo sequence (HASTE) with deep learning (DL) reconstruction for ultrafast imaging of the bladder with reduced susceptibility to motion artifac...

Predicting clozapine-induced adverse drug reaction biomarkers using machine learning.

Scientific reports
Clozapine is an atypical antipsychotic used for patients with treatment-resistant schizophrenia. This drug has serious adverse drug reactions (ADRs), including the risk of severe neutropenia (agranulocytosis). Patients who could benefit from clozapin...

Developing angiogenesis-related prognostic biomarkers and therapeutic strategies in bladder cancer using deep learning and machine learning.

Scientific reports
Bladder cancer (BLCA) is a prevalent urological malignancy that exhibits a high degree of tumor heterogeneity and morbidity. Tumor angiogenesis, a vital hallmark of cancer, greatly influences the tumor microenvironment (TME). The emergence of anti-an...

Objective monitoring of motor symptom severity and their progression in Parkinson's disease using a digital gait device.

Scientific reports
Digital technologies for monitoring motor symptoms of Parkinson's Disease (PD) underwent a strong evolution during the past years. Although it has been shown for several devices that derived digital gait features can reliably discriminate between hea...

Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer.

Scientific reports
Although neoadjuvant chemotherapy with docetaxel + cisplatin + 5-fluorouracil (CF) has been the standard treatment for stage II and III esophageal cancers, it is associated with severe adverse events caused by docetaxel. Consequently, this study aime...

Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population.

Scientific reports
Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to cat...

Preoperative prediction value of 2.5D deep learning model based on contrast-enhanced CT for lymphovascular invasion of gastric cancer.

Scientific reports
To develop and validate artificial intelligence models based on contrast-enhanced CT(CECT) images of venous phase using deep learning (DL) and Radiomics approaches to predict lymphovascular invasion in gastric cancer prior to surgery. We retrospectiv...

Evaluating cognitive decline detection in aging populations with single-channel EEG features based on two studies and meta-analysis.

Scientific reports
Timely detection of cognitive decline is paramount for effective intervention, prompting researchers to leverage EEG pattern analysis, focusing particularly on cognitive load, to establish reliable markers for early detection and intervention. This c...

Utilizing CBNet to effectively address and combat cyberbullying among university students on social media platforms.

Scientific reports
Cyberbullying can profoundly impact individuals' mental health, leading to increased feelings of anxiety, depression, and social isolation. Psychological research suggests that cyberbullying victims may experience long-term psychological consequences...

Poincare guided geometric UNet for left atrial epicardial adipose tissue segmentation in Dixon MRI images.

Scientific reports
Epicardial Adipose Tissue (EAT) is a recognized risk factor for cardiovascular diseases and plays a pivotal role in the pathophysiology of Atrial Fibrillation (AF). Accurate automatic segmentation of the EAT around the Left Atrium (LA) from Magnetic ...