AIMC Topic: Humans

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MCTASmRNA: A deep learning framework for alternative splicing events classification.

International journal of biological macromolecules
Alternative splicing (AS) plays crucial post-transcriptional gene function regulation roles in eukaryotic. Despite progress in studying AS at the RNA level, existing methods for AS event identification face challenges such as inefficiency, lengthy pr...

Biocomputing at the crossroad between emulating artificial intelligence and cellular supremacy.

Current opinion in biotechnology
Biocomputation aims to create sophisticated biological systems capable of addressing important problems in (bio)medicine with a machine-like precision. At present, computational gene networks engineered by single- or multi-layered assembly of DNA-, R...

Machine learning demonstrates clinical utility in distinguishing retinoblastoma from pseudo retinoblastoma with RetCam images.

Ophthalmic genetics
BACKGROUND: Retinoblastoma is diagnosed and treated without biopsy based solely on appearance (with the indirect ophthalmoscope and imaging). More than 20 benign ophthalmic disorders resemble retinoblastoma and errors in diagnosis continue to be made...

Deep learning-based MVIT-MLKA model for accurate classification of pancreatic lesions: a multicenter retrospective cohort study.

La Radiologia medica
BACKGROUND: Accurate differentiation between benign and malignant pancreatic lesions is critical for effective patient management. This study aimed to develop and validate a novel deep learning network using baseline computed tomography (CT) images t...

Covariate Model Selection Approaches for Population Pharmacokinetics: A Systematic Review of Existing Methods, From SCM to AI.

CPT: pharmacometrics & systems pharmacology
A growing number of covariate modeling methods have been proposed in the field of popPK modeling, but limited information exists on how they all compare. The objective of this study was to perform a systematic review of all popPK covariate modeling m...

Predictors of glycaemic improvement in children and young adults with type 1 diabetes and very elevated HbA1c using the MiniMed 780G system.

Diabetes, obesity & metabolism
AIMS: This study aimed to identify key factors with the greatest influence on glycaemic outcomes in young individuals with type 1 diabetes (T1D) and very elevated glycaemia after 3 months of automated insulin delivery (AID).

Machine Learning-Assisted Prediction of Photothermal Metal-Phenolic Networks.

Angewandte Chemie (International ed. in English)
Photothermal therapy (PTT) demonstrates significant potential in cancer treatment, wound healing, and antibacterial therapy, with its efficacy largely depending on the performance of photothermal agents (PTAs). Metal-phenolic network (MPN) materials ...

Opportunistic AI for enhanced cardiovascular disease risk stratification using abdominal CT scans.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This study introduces the Deep Learning-based Cardiovascular Disease Incident (DL-CVDi) score, a novel biomarker derived from routine abdominal CT scans, optimized to predict cardiovascular disease (CVD) risk using deep survival learning. CT imaging,...

Perspective: Multiomics and Artificial Intelligence for Personalized Nutritional Management of Diabetes in Patients Undergoing Peritoneal Dialysis.

Advances in nutrition (Bethesda, Md.)
Managing diabetes in patients on peritoneal dialysis (PD) is challenging due to the combined effects of dietary glucose, glucose from dialysate, and other medical complications. Advances in technology that enable continuous biological data collection...

Demystifying artificial intelligence for veterinary professionals: practical applications and future potential.

American journal of veterinary research
The field of veterinary medicine, like many others, is expected to undergo a significant transformation due to artificial intelligence (AI), although the full extent remains unclear. Artificial intelligence is already becoming prominent throughout da...