AIMC Topic: Precision Medicine

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Recent Advances in Artificial Intelligence to Improve Immunotherapy and the Use of Digital Twins to Identify Prognosis of Patients with Solid Tumors.

International journal of molecular sciences
To date, the public health system has been impacted by the increasing costs of many diagnostic and therapeutic pathways due to limited resources. At the same time, we are constantly seeking to improve these paths through approaches aimed at personali...

The role of artificial intelligence in the management of liver diseases.

The Kaohsiung journal of medical sciences
Universal neonatal hepatitis B virus (HBV) vaccination and the advent of direct-acting antivirals (DAA) against hepatitis C virus (HCV) have reshaped the epidemiology of chronic liver diseases. However, some aspects of the management of chronic liver...

Artificial intelligence for predicting treatment responses in autoimmune rheumatic diseases: advancements, challenges, and future perspectives.

Frontiers in immunology
Autoimmune rheumatic diseases (ARD) present a significant global health challenge characterized by a rising prevalence. These highly heterogeneous diseases involve complex pathophysiological mechanisms, leading to variable treatment efficacies across...

Future of allergy and immunology: Is artificial intelligence the key in the digital era?

Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology
Artificial intelligence (AI) is reshaping allergy and immunology by integrating cutting-edge technology to enhance patient outcomes and redefine clinical practices and research. This review evaluates AI's evolving role, emphasizing its impact on diag...

Intelligent revolution in medicine - the application of artificial intelligence (ai) in medicine: overview, benefits, and challenges.

Przeglad epidemiologiczny
Artificial Intelligence (AI) has the potential to revolutionize medical diagnostics by offering new opportunities for accuracy, efficiency, and accessibility in healthcare. This article examines the benefits of implementing AI in diagnostics, such as...

Unlocking therapeutic frontiers: harnessing artificial intelligence in drug discovery for neurodegenerative diseases.

Drug discovery today
Neurodegenerative diseases (NDs) pose serious healthcare challenges with limited therapeutic treatments and high social burdens. The integration of artificial intelligence (AI) into drug discovery has emerged as a promising approach to address these ...

Challenges and applications in generative AI for clinical tabular data in physiology.

Pflugers Archiv : European journal of physiology
Recent advancements in generative approaches in AI have opened up the prospect of synthetic tabular clinical data generation. From filling in missing values in real-world data, these approaches have now advanced to creating complex multi-tables. This...

Deep Reinforcement Learning for personalized diagnostic decision pathways using Electronic Health Records: A comparative study on anemia and Systemic Lupus Erythematosus.

Artificial intelligence in medicine
BACKGROUND: Clinical diagnoses are typically made by following a series of steps recommended by guidelines that are authored by colleges of experts. Accordingly, guidelines play a crucial role in rationalizing clinical decisions. However, they suffer...

Precision Epidemiology: A Computational Analysis of the Impact of Algorithmic Prediction on the Relationship Between Population Epidemiology and Clinical Epidemiology.

International journal of public health
OBJECTIVES: Precision Medicine (PM) uses advanced Machine Learning (ML) techniques and big data to develop personalized treatments, but healthcare still relies on traditional statistical procedures not targeted on individuals. This study investigates...

Personalized prediction of immunotherapy response in lung cancer patients using advanced radiomics and deep learning.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Lung cancer (LC) is a leading cause of cancer-related mortality, and immunotherapy (IO) has shown promise in treating advanced-stage LC. However, identifying patients likely to benefit from IO and monitoring treatment response remains cha...