AIMC Topic: Algorithms

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Maximizing Lung Cancer Screening in High-Risk Population Leveraging ML-Developed Risk-Prediction Algorithms: Danish Retrospective Validation of LungFlag.

Clinical lung cancer
BACKGROUND: Early detection of lung cancer (LC) is crucial for curative treatment, but current screening methods face challenges due to high costs and poor adherence. Artificial intelligence tools, such as the LungFlag model, uses routine clinical da...

Automated phenotypic analysis and classification of drug-treated cardiomyocytes via synergized time-lapse holographic imaging and deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Predicting cardiovascular risk is critical for the therapy and control of cardiovascular illnesses. This work studies screening the toxicity of three drugs, (E-4031, isoprenaline, and sertindole) with various concentrations ...

Lesion boundary detection for skin lesion segmentation based on boundary sensing and CNN-transformer fusion networks.

Artificial intelligence in medicine
Traditional convolutional neural networks often struggle to capture global information and handle ambiguous boundaries during complex skin lesion segmentation tasks. To tackle this challenge, we proposed MPBA-Net, a hybrid network that integrates mul...

Comparison among artificial intelligence-based age estimation from morphological analysis of the pubic symphysis versus experienced and novice practitioners using a new atlas for component labeling.

International journal of legal medicine
Traditional age estimation methods based on macroscopic observation has been criticized for being excessively dependent on the observer's experience. The aim of this technical note is to propose a new atlas to assist the forensic practitioner in labe...

Predicting clinical outcomes using 18F-FDG PET/CT-based radiomic features and machine learning algorithms in patients with esophageal cancer.

Nuclear medicine communications
OBJECTIVE: This study evaluated the relationship between 18F-fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) radiomic features and clinical parameters, including tumor localization, histopathological subtype, lymph node metastasis, mortal...

Angular correlation-based feature selection for machine learning classification of manual automatisms using body sensor network data.

Computers in biology and medicine
Automatisms are repetitive, semi-ordered movements often observed in focal impaired awareness seizures and, less frequently, in generalized seizures with brief loss of consciousness. This study aims to improve the detection of these automatisms by op...

Shining Light on DNA Mutations through Machine Learning-Augmented Vibrational Spectroscopy.

Analytical chemistry
A method to directly predict the number of nucleic acid bases in a single-stranded DNA (ssDNA) or a genomic DNA has been proposed with a combination of Raman spectroscopy and an Artificial Neural Network (ANN) algorithm. In this work, the algorithm w...

Machine reading and recovery of colors for hemoglobin-related bioassays and bioimaging.

Science advances
Despite advances in machine learning and computer vision for biomedical imaging, machine reading and learning of colors remain underexplored. Color consistency in computer vision, color constancy in human perception, and color accuracy in biomedical ...

GNNMutation: a heterogeneous graph-based framework for cancer detection.

BMC bioinformatics
BACKGROUND: When genes are translated into proteins, mutations in the gene sequence can lead to changes in protein structure and function as well as in the interactions between proteins. These changes can disrupt cell function and contribute to the d...

HLN-DDI: hierarchical molecular representation learning with co-attention mechanism for drug-drug interaction prediction.

BMC bioinformatics
BACKGROUND: Accurate identification of drug-drug interactions (DDIs) is critical in pharmacology, as DDIs can either enhance therapeutic efficacy or trigger adverse reactions when multiple medications are administered concurrently. Traditional method...