AIMC Topic: Humans

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Optimizing Bi-LSTM networks for improved lung cancer detection accuracy.

PloS one
Lung cancer remains a leading cause of cancer-related deaths worldwide, with low survival rates often attributed to late-stage diagnosis. To address this critical health challenge, researchers have developed computer-aided diagnosis (CAD) systems tha...

Development and validation of predictive models for diabetic retinopathy using machine learning.

PloS one
OBJECTIVE: This study aimed to develop and compare machine learning models for predicting diabetic retinopathy (DR) using clinical and biochemical data, specifically logistic regression, random forest, XGBoost, and neural networks.

Integrative analysis of mitochondrial and immune pathways in diabetic kidney disease: identification of AASS and CASP3 as key predictors and therapeutic targets.

Renal failure
OBJECTIVES: Diabetic kidney disease (DKD) is driven by mitochondrial dysfunction and immune dysregulation, yet the mechanistic interplay remains poorly defined. This study aimed to identify key molecular networks linking mitochondrial and immune path...

[MP-MRI in the evaluation of non-operative treatment response, for residual and recurrent tumor detection in head and neck cancer].

Magyar onkologia
As non-surgical therapies gain acceptance in head and neck tumors, the importance of imaging has increased. New therapeutic methods (in radiation therapy, targeted biological therapy, immunotherapy) need better tumor characterization and prognostic i...

Intraoperative stenosis detection in X-ray coronary angiography via temporal fusion and attention-based CNN.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND AND OBJECTIVE: Coronary artery disease (CAD), the leading cause of mortality, is caused by atherosclerotic plaque buildup in the arteries. The gold standard for the diagnosis of CAD is via X-ray coronary angiography (XCA) during percutaneo...

Bridging gaps in artificial intelligence adoption for maternal-fetal and obstetric care: Unveiling transformative capabilities and challenges.

Computer methods and programs in biomedicine
PURPOSE: This review aims to comprehensively explore the application of Artificial Intelligence (AI) to an area that has not been traditionally explored in depth: the continuum of maternal-fetal health. In doing so, the intent was to examine this phy...

Cooperative GAN: Automated tympanic membrane anomaly detection using a Cooperative Observation Network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Recently, artificial intelligence (AI) has been applied to otolaryngology. However, existing supervised learning methods cannot easily predict data outside the learning domain. Moreover, collecting diverse medical data has ...

Hypothesis: Net benefit as an objective function during development of machine learning algorithms for medical applications.

International journal of medical informatics
Net benefit is the most widely used metric for evaluating the clinical utility of medical prediction models. The approach applies decision analytic theory to weight true and false positives depending on the relative consequences of different decision...

Resveratrol in animal models of pancreatitis and pancreatic cancer: A systematic review with machine learning.

Phytomedicine : international journal of phytotherapy and phytopharmacology
BACKGROUND: Resveratrol (RES), a common type of plant polyphenols, has demonstrated promising therapeutic efficacy and safety in animal models of pancreatitis and pancreatic cancer. However, a comprehensive analysis of these data is currently unavail...

A new era of psoriasis treatment: Drug repurposing through the lens of nanotechnology and machine learning.

International journal of pharmaceutics
Psoriasis is a persistent inflammatory skin disorder characterized by hyper-proliferation and abnormal epidermal differentiation. Conventional treatments such as; topical therapies, phototherapy, systemic immune modulators, and biologics aim to relie...