AIMC Topic: Precision Medicine

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Need Analysis of Clinician-Oriented Integrated Precision Oncology Decision Support Tools: Qualitative Descriptive Study.

JMIR human factors
BACKGROUND: The rapid advancement of next-generation sequencing has significantly expanded the landscape of precision medicine. However, health care professionals face increasing challenges in keeping pace with the growing body of oncological knowled...

Personalized health monitoring using explainable AI: bridging trust in predictive healthcare.

Scientific reports
AI has propelled the potential for moving toward personalized health and early prediction of diseases. Unfortunately, a significant limitation of many of these deep learning models is that they are not interpretable, restricting their clinical utilit...

Machine learning-based penetrance of genetic variants.

Science (New York, N.Y.)
Accurate variant penetrance estimation is crucial for precision medicine. We constructed machine learning (ML) models for 10 diseases using 1,347,298 participants with electronic health records, then applied them to an independent cohort with linked ...

Immune profiling in oncology: bridging the gap between technology and treatment.

Medical oncology (Northwood, London, England)
Immune profiling has become a transformative tool in oncology, offering comprehensive information on tumor immune interactions and facilitating precision medicine. Recent advances such as mass cytometry (CyTOF), single-cell RNA sequencing (scRNA-seq)...

Increasing pathogenic germline variant diagnosis rates in precision medicine: current best practices and future opportunities.

Human genomics
The accurate diagnosis of pathogenic variants is essential for effective clinical decision making within precision medicine programs. Despite significant advances in both the quality and quantity of molecular patient data, diagnostic rates remain sub...

Toward Sex-Specific Biomaterials Innovation: A Perspective.

ACS biomaterials science & engineering
Sex-related differences influence key biological processes relevant to biomaterials research, including tissue regeneration, immune response, drug metabolism, and relevant diseases. Despite increasing recognition of sex as a critical biological varia...

Personalized blood glucose prediction in type 1 diabetes using meta-learning with bidirectional long short term memory-transformer hybrid model.

Scientific reports
Personalized blood glucose (BG) prediction in Type 1 Diabetes (T1D) is challenged by significant inter-patient heterogeneity. To address this, we propose BiT-MAML, a hybrid model combining a Bidirectional LSTM-Transformer with Model-Agnostic Meta-Lea...

Transforming sepsis management: AI-driven innovations in early detection and tailored therapies.

Critical care (London, England)
Sepsis remains a leading cause of mortality worldwide, driven by its clinical complexity and delayed recognition. Artificial intelligence (AI) offers promising solutions to improve sepsis care through earlier detection, risk stratification, and perso...

Machine learning-based construction of Immunogenic cell death-related score for improving prognosis and personalized treatment in glioma.

Scientific reports
Immunogenic cell death (ICD) is capable of activating both innate and adaptive immune responses. In this study, we aimed to develop an ICD-related signature in glioma patients and facilitate the assessment of their prognosis and drug sensitivity. Con...

Multiphysics modelling enhanced by imaging and artificial intelligence for personalised cancer nanomedicine: Foundations for clinical digital twins.

Journal of controlled release : official journal of the Controlled Release Society
Nano-sized drug delivery systems have emerged as a more effective, versatile means for improving cancer treatment. However, the complexity of drug delivery to cancer involves intricate interactions between physiological and physicochemical processes ...