AIMC Topic: Precision Medicine
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Hybridizing mechanistic modeling and deep learning for personalized survival prediction after immune checkpoint inhibitor immunotherapy.
NPJ systems biology and applications
Aug 14, 2024
We present a study where predictive mechanistic modeling is combined with deep learning methods to predict individual patient survival probabilities under immune checkpoint inhibitor (ICI) immunotherapy. This hybrid approach enables prediction based ...
Characterization of cardiac resynchronization therapy response through machine learning and personalized models.
Computers in biology and medicine
Aug 13, 2024
INTRODUCTION: The characterization and selection of heart failure (HF) patients for cardiac resynchronization therapy (CRT) remain challenging, with around 30% non-responder rate despite following current guidelines. This study aims to propose a nove...
Cancer cytogenetics in the era of artificial intelligence: shaping the future of chromosome analysis.
Future oncology (London, England)
Aug 12, 2024
Artificial intelligence (AI) has rapidly advanced in the past years, particularly in medicine for improved diagnostics. In clinical cytogenetics, AI is becoming crucial for analyzing chromosomal abnormalities and improving precision. However, existin...
[Healthcare 4.0-Medicine in transition].
Herz
Aug 8, 2024
Healthcare 4.0 describes the future transformation of the healthcare sector driven by the combination of digital technologies, such as artificial intelligence (AI), big data and the Internet of Medical Things, enabling the advancement of precision me...
CPU-GPU Cooperative QoS Optimization of Personalized Digital Healthcare Using Machine Learning and Swarm Intelligence.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2024
In recent decades, the rapid advances in information technology have promoted a widespread deployment of medical cyber-physical systems (MCPS), especially in the area of digital healthcare. In digital healthcare, medical edge devices empowered by CPU...
Emerging Analytical Approaches for Personalized Medicine Using Machine Learning In Pediatric and Congenital Heart Disease.
The Canadian journal of cardiology
Aug 7, 2024
Precision and personalized medicine, the process by which patient management is tailored to individual circumstances, are now terms that are familiar to cardiologists, despite it still being an emerging field. Although precision medicine relies most ...
Toward Realizing the Promise of AI in Precision Health Across the Spectrum of Care.
Annual review of genomics and human genetics
Aug 6, 2024
Significant progress has been made in augmenting clinical decision-making using artificial intelligence (AI) in the context of secondary and tertiary care at large academic medical centers. For such innovations to have an impact across the spectrum o...
Personalized approach to malignant struma ovarii: Insights from a web-based machine learning tool.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Aug 4, 2024
OBJECTIVES: Malignant struma ovarii (MSO) is a rare ovarian tumor characterized by mature thyroid tissue. The diverse symptoms and uncommon nature of MSO can create difficulties in its diagnosis and treatment. This study aimed to analyze data and use...
Transforming Health Care Landscapes: The Lever of Radiology Research and Innovation on Emerging Markets Poised for Aggressive Growth.
Journal of the American College of Radiology : JACR
Aug 2, 2024
Advances in radiology are crucial not only to the future of the field but to medicine as a whole. Here, we present three emerging areas of medicine that are poised to change how health care is delivered-hospital at home, artificial intelligence, and ...
Machine Learning Methods to Estimate Individualized Treatment Effects for Use in Health Technology Assessment.
Medical decision making : an international journal of the Society for Medical Decision Making
Jul 26, 2024
BACKGROUND: Recent developments in causal inference and machine learning (ML) allow for the estimation of individualized treatment effects (ITEs), which reveal whether treatment effectiveness varies according to patients' observed covariates. ITEs ca...
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