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Feedback Attention to Enhance Unsupervised Deep Learning Image Registration in 3D Echocardiography.

IEEE transactions on medical imaging
Cardiac motion estimation is important for assessing the contractile health of the heart, and performing this in 3D can provide advantages due to the complex 3D geometry and motions of the heart. Deep learning image registration (DLIR) is a robust wa...

High-Resolution Maps of Left Atrial Displacements and Strains Estimated With 3D Cine MRI Using Online Learning Neural Networks.

IEEE transactions on medical imaging
The functional analysis of the left atrium (LA) is important for evaluating cardiac health and understanding diseases like atrial fibrillation. Cine MRI is ideally placed for the detailed 3D characterization of LA motion and deformation but is lackin...

Predictive survival modelings for HIV-related cryptococcosis: comparing machine learning approaches.

Frontiers in cellular and infection microbiology
INTRODUCTION: HIV-associated cryptococcosis is marked by unpredictable disease trajectories and persistently high mortality rates worldwide. Although improved risk stratification and tailored clinical management are urgently needed to enhance patient...

High-Granularity Machine Learning Prediction of Acute Brain Injury in Patients Receiving Venoarterial Extracorporeal Membrane Oxygenation.

ASAIO journal (American Society for Artificial Internal Organs : 1992)
Acute brain injury (ABI) is prevalent among patients undergoing venoarterial extracorporeal membrane oxygenation (VA-ECMO) and significantly impact recovery. Early prediction of ABI could enable timely interventions to prevent adverse outcomes, but e...

Predicting children's emotional and behavioral difficulties at age five using pregnancy and newborn risk factors: Evidence from the UK Household Longitudinal Study.

Journal of affective disorders
Childhood emotional and behavioral difficulties have a profound impact on later life outcomes, making it crucial to identify early-life risk factors that predict emotional and behavioral difficulties. However, much of the existing research has concen...

Development and Validation of a Cell-Free DNA Fragmentomics-Based Model for Early Detection of Pancreatic Cancer.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE: Pancreatic ductal adenocarcinoma (PDAC), known for its high fatality rate, is often diagnosed in its advanced stages where surgical options are not viable. This highlights the critical need for innovative and effective early detection techni...

Reirradiation for recurrent glioblastoma: the significance of the residual tumor volume.

Journal of neuro-oncology
PURPOSE: Recurrent glioblastoma has a poor prognosis, and its optimal management remains unclear. Reirradiation (re-RT) is a promising treatment option, but long-term outcomes and optimal patient selection criteria are not well established.

Forecasting optimal treatments in relapsed/refractory mature T- and NK-cell lymphomas: A global PETAL Consortium study.

British journal of haematology
There is no standard of care in relapsed/refractory T-cell/natural killer-cell lymphomas. Patients often cycle through cytotoxic chemotherapy (CC), epigenetic modifiers (EM) or small molecule inhibitors (SMI) empirically. Ideal therapy at each line r...

Machine Learning for Predicting Critical Events Among Hospitalized Children.

JAMA network open
IMPORTANCE: Unrecognized deterioration among hospitalized children is associated with a high risk of mortality and morbidity. The current approach to pediatric risk stratification is fragmented, as each hospital unit (emergency, ward, or intensive ca...

Dedicated AI Expert System vs Generative AI With Large Language Model for Clinical Diagnoses.

JAMA network open
IMPORTANCE: Large language models (LLMs) have not yet been compared with traditional diagnostic decision support systems (DDSSs) on unpublished clinical cases.