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Single-cell hdWGCNA reveals metastatic protective macrophages and development of deep learning model in uveal melanoma.

Journal of translational medicine
BACKGROUND: Although there has been some progress in the treatment of primary uveal melanoma (UVM), distant metastasis remains the leading cause of death in patients. Monitoring, staging, and treatment of metastatic disease have not yet reached conse...

Interpretable machine learning models for predicting clinical pregnancies associated with surgical sperm retrieval from testes of different etiologies: a retrospective study.

BMC urology
BACKGROUND: The relationship between surgical sperm retrieval of different etiologies and clinical pregnancy is unclear. We aimed to develop a robust and interpretable machine learning (ML) model for predicting clinical pregnancy using the SHapley Ad...

Predicting graft and patient outcomes following kidney transplantation using interpretable machine learning models.

Scientific reports
The decision to accept a deceased donor organ offer for transplant, or wait for something potentially better in the future, can be challenging. Clinical decision support tools predicting transplant outcomes are lacking. This project uses interpretabl...

Communicating exploratory unsupervised machine learning analysis in age clustering for paediatric disease.

BMJ health & care informatics
BACKGROUND: Despite the increasing availability of electronic healthcare record (EHR) data and wide availability of plug-and-play machine learning (ML) Application Programming Interfaces, the adoption of data-driven decision-making within routine hos...

Spiking Laguerre Volterra networks-predicting neuronal activity from local field potentials.

Journal of neural engineering
Understanding the generative mechanism between local field potentials (LFP) and neuronal spiking activity is a crucial step for understanding information processing in the brain. Up to now, most approaches have relied on simply quantifying the coupli...

Prediction of post-donation renal function using machine learning techniques and conventional regression models in living kidney donors.

Journal of nephrology
BACKGROUND: Accurate prediction of renal function following kidney donation and careful selection of living donors are essential for living-kidney donation programs. We aimed to develop a prediction model for post-donation renal function following li...

Natural language processing in at-risk mental states: enhancing the assessment of thought disorders and psychotic traits with semantic dynamics and graph theory.

Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)
OBJECTIVE: Verbal communication contains key information for mental health assessment. Researchers have linked psychopathology phenomena to certain counterparts in natural language processing. We characterized subtle impairments in the early stages o...

Diagnosing the Severity of Knee Osteoarthritis Using Regression Scores From Artificial Intelligence Convolution Neural Networks.

Orthopedics
BACKGROUND: This study focused on using deep learning neural networks to classify the severity of osteoarthritis in the knee. A continuous regression score of osteoarthritis severity has yet to be explored using artificial intelligence machine learni...

Clinical utility of a rapid two-dimensional balanced steady-state free precession sequence with deep learning reconstruction.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular magnetic resonance (CMR) cine imaging is still limited by long acquisition times. This study evaluated the clinical utility of an accelerated two-dimensional (2D) cine sequence with deep learning reconstruction (Sonic DL) t...

Deep learning approach for unified recognition of driver speed and lateral intentions using naturalistic driving data.

Neural networks : the official journal of the International Neural Network Society
Driver intention recognition is a critical component of advanced driver assistance systems, with significant implications for improving vehicle safety, intelligence, and fuel economy. However, previous research on driver intention recognition has not...