AI Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

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Identification of potential biomarkers for lung cancer using integrated bioinformatics and machine learning approaches.

PloS one
Lung cancer is one of the most common cancer and the leading cause of cancer-related death worldwide. Early detection of lung cancer can help reduce the death rate; therefore, the identification of potential biomarkers is crucial. Thus, this study ai...

Adaptive control and state error prediction of flexible manipulators using radial basis function neural network and dynamic surface control method.

PloS one
This paper introduces a novel control strategy for managing the uncertainties in flexible joint manipulators, incorporating a Radial Basis Function Neural Network (RBFNN) with Adaptive Dynamic Surface Control (ADSC). This strategy innovatively utiliz...

Author name disambiguation based on heterogeneous graph neural network.

PloS one
With the dramatic increase in the number of published papers and the continuous progress of deep learning technology, the research on name disambiguation is at a historic peak, the number of paper authors is increasing every year, and the situation o...

Machine learning-based prediction of distant metastasis risk in invasive ductal carcinoma of the breast.

PloS one
More than 90% of deaths due to breast cancer (BC) are due to metastasis-related complications, with invasive ductal carcinoma (IDC) of the breast being the most common pathologic type of breast cancer and highly susceptible to metastasis to distant o...

Enhancing the decision optimization of interaction design in sustainable healthcare with improved artificial bee colony algorithm and generative artificial intelligence.

PloS one
With the development of digital health, enhancing decision-making effectiveness has become a critical task. This study proposes an improved Artificial Bee Colony (ABC) algorithm aimed at optimizing decision-making models in the field of digital healt...

Machine learning for predicting antimicrobial resistance in critical and high-priority pathogens: A systematic review considering antimicrobial susceptibility tests in real-world healthcare settings.

PloS one
BACKGROUND: Antimicrobial resistance (AMR) poses a worldwide health threat; quick and accurate identification of AMR enhances patient outcomes and reduces inappropriate antibiotic usage. The objective of this systematic review is to evaluate the effi...

Assessing regional competitiveness in Peru: An approach using nonlinear machine learning models.

PloS one
This study addresses the challenges of measuring regional competitiveness using traditional methods, due to the inherent complexity and non-linearity of its determinants'. The development of new Machine Learning (ML) models allows the creation of pre...

Chinese medical named entity recognition utilizing entity association and gate context awareness.

PloS one
Recognizing medical named entities is a crucial aspect of applying deep learning in the medical domain. Automated methods for identifying specific entities from medical literature or other texts can enhance the efficiency and accuracy of information ...

Advanced computational approaches for predicting sunflower yield: Insights from ANN, ANFIS, and GEP in normal and salinity stress environments.

PloS one
Prediction of crop yield is essential for decision-makers to ensure food security and provides valuable information to farmers about factors affecting high yields. This research aimed to predict sunflower grain yield under normal and salinity stress ...

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...