Latest AI and machine learning research in refractive surgery for healthcare professionals.
Post-mortem diffusion MRI plays a key role in investigative pipelines to characterise tissue microstructure, with long scan times facilitating the acquisition of datasets with improved spatial/angular resolution and reduced artefacts versus in vivo. Diffusion-weighted steady-state free precession (DW-SSFP) has emerged as a powerful technique for post-mortem imaging, achieving high SNR-efficiency a...
The application of artificial intelligence (AI)/machine learning (ML) to MRI can be a powerful tool to streamline clinical decision-making, yet variability amongst MRI sequences and algorithms have hindered appropriate assessment of reliability and generalizability. We conducted a systematic review and meta-analysis of the ability of current AI/ML models operating on MRI data for: 1) epilepsy diag...
Accurate identification of the seizure onset zone (SOZ) using intracranial electroencephalography (iEEG) remains challenging. Although diverse methods...
Immoral decisions, which engage both cognitive control and reward system, bring both cognitive and neural consequences. However, how dishonesty has an...
Genomic functions arise from nucleotide sequences and their overlapping k-mers – subsequences whose contributions depend on their composition, positio...
Organisation and dynamics of chromatin play a key role in regulation of cell state and function. In cancer, chromatin plasticity is known to be import...
Genomic prediction and design require models that integrate local sequence features with long-range regulatory dependencies spanning hundreds of kilob...
For patients with facial paralysis, the wait for return of facial function and resulting vision risk from poor eye closure, difficulty speaking and ea...
Emerging evidence indicates an elevated risk of post-concussion musculoskeletal (MSK) injuries in collegiate athletes; however, identifying athletes a...
Artificial intelligence (AI) foundation models such as Segment Anything Model 2 (SAM 2) offer potential for semi-automated image segmentation with min...
To evaluate the potential of wrist-worn wearable devices to detect and quantify Faciobrachial Dystonic Seizures (FBDS) and related events associated w...
Post-Traumatic Stress Disorder (PTSD) is a debilitating mental health condition commonly treated with medications like benzodiazepines (BZDs), despite...
Machine learning-generated segmentations of the trigeminal nerve and nearby blood vessels have the potential to quantify the magnitude of neurovascula...
Spontaneous intracranial hemorrhages have a high disease burden. Due to increasing medical imaging, new technological solutions for assisting in image...
Patients with post-COVID-19-related symptoms require active and timely support in self-management. Just-in-time adaptive interventions (JITAI) seem pr...
Intraoperative hypotension burden not equally distributed during various periods of a general anesthetic. Post-induction hypotension usually has an ia...
Extracellular vesicles (EVs) are lipid nano-to-micro-sized vesicles increasingly identified as valuable liquid biopsy tools for medical applications. ...
An accurate, robust, clinically accessible, and explainable predictive model for post-stroke composite outcomes could identify high-risk patients for ...
Mpox, caused by mpox virus (MPXV), has gained global attention following the 2022 Clade IIb outbreak and the emergence of two novel Clade I lineages i...
Precision-guided dual antiplatelet therapy (DAPT) duration post-percutaneous coronary intervention (PCI) remains a clinical challenge. Current risk st...