AIMC Topic: Algorithms

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Wrinkle force microscopy: a machine learning based approach to predict cell mechanics from images.

Communications biology
Combining experiments with artificial intelligence algorithms, we propose a machine learning based approach called wrinkle force microscopy (WFM) to extract the cellular force distributions from the microscope images. The full process can be divided ...

Benchmarking of deep learning algorithms for 3D instance segmentation of confocal image datasets.

PLoS computational biology
Segmenting three-dimensional (3D) microscopy images is essential for understanding phenomena like morphogenesis, cell division, cellular growth, and genetic expression patterns. Recently, deep learning (DL) pipelines have been developed, which claim ...

COVID Detection From Chest X-Ray Images Using Multi-Scale Attention.

IEEE journal of biomedical and health informatics
Deep learning based methods have shown great promise in achieving accurate automatic detection of Coronavirus Disease (covid) - 19 from Chest X-Ray (cxr) images.However, incorporating explainability in these solutions remains relatively less explored...

Dynamic Neural Graphs Based Federated Reptile for Semi-Supervised Multi-Tasking in Healthcare Applications.

IEEE journal of biomedical and health informatics
AI healthcare applications rely on sensitive electronic healthcare records (EHRs) that are scarcely labelled and are often distributed across a network of the symbiont institutions. It is challenging to train the effective machine learning models on ...

AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy.

IEEE journal of biomedical and health informatics
Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results will hamper timely follow-up which is crucial to the patients' treatment...

Learning Multi-Scale Heterogeneous Representations and Global Topology for Drug-Target Interaction Prediction.

IEEE journal of biomedical and health informatics
Identification of interactions between drugs and target proteins plays a critical role not only in drug discovery but also in drug repositioning. Deep integration of inter-connections and intra-similarities between heterogeneous multi-source data abo...

Time-Frequency Analysis of Scalp EEG With Hilbert-Huang Transform and Deep Learning.

IEEE journal of biomedical and health informatics
Electroencephalography (EEG) is a brain imaging approach that has been widely used in neuroscience and clinical settings. The conventional EEG analyses usually require pre-defined frequency bands when characterizing neural oscillations and extracting...

A Meta-Learning Approach for Fast Personalization of Modality Translation Models in Wearable Physiological Sensing.

IEEE journal of biomedical and health informatics
Modality translation grants diagnostic value to wearable devices by translating signals collected from low-power sensors to their highly-interpretable counterparts that are more familiar to healthcare providers. For instance, bio-impedance (Bio-Z) is...

Predicting Brain Age Using Machine Learning Algorithms: A Comprehensive Evaluation.

IEEE journal of biomedical and health informatics
Machine learning (ML) algorithms play a vital role in the brain age estimation frameworks. The impact of regression algorithms on prediction accuracy in the brain age estimation frameworks have not been comprehensively evaluated. Here, we sought to a...

Implementing Critical Machine Learning (ML) Approaches for Generating Robust Discriminative Neuroimaging Representations Using Structural Equation Model (SEM).

Computational and mathematical methods in medicine
Critical ML or CML is a critical approach development of the standard ML (SML) procedure. Conventional ML (ML) is being used in radiology departments where complex neuroimages are discriminated using ML technology. Radiologists and researchers found ...