AIMC Topic: Humans

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Developing Affordable, Portable and Simplistic Diagnostic Sensors to Improve Access to Care.

Sensors (Basel, Switzerland)
Ophthalmology is a highly technical specialty, especially in the area of diagnostic equipment. While the field is innovative, the access to cutting-edge technology is limited with reference to the global population. A significant way to improve overa...

Clinical language search algorithm from free-text: facilitating appropriate imaging.

BMC medical imaging
BACKGROUND: The comprehensiveness and maintenance of the American College of Radiology (ACR) Appropriateness Criteria (AC) makes it a unique resource for evidence-based clinical imaging decision support, but it is underutilized by clinicians. To faci...

Task-Coupling Elastic Learning for Physical Sign-Based Medical Image Classification.

IEEE journal of biomedical and health informatics
Physical signs of patients indicate crucial evidence for diagnosing both location and nature of the disease, where there is a sequential relationship between the two tasks. Thus their joint learning can utilize intrinsic association by transferring r...

Medical Instrument Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning.

IEEE journal of biomedical and health informatics
Medical instrument segmentation in 3D ultrasound is essential for image-guided intervention. However, to train a successful deep neural network for instrument segmentation, a large number of labeled images are required, which is expensive and time-co...

Anomalous Gait Feature Classification From 3-D Motion Capture Data.

IEEE journal of biomedical and health informatics
The gait kinematics of an individual is affected by various factors, including age, anthropometry, gender, and disease. Detecting anomalous gait features aids in the diagnosis and treatment of gait-related diseases. The objective of this study was to...

Geometric Deep Learning for Subject Independent Epileptic Seizure Prediction Using Scalp EEG Signals.

IEEE journal of biomedical and health informatics
Recently, researchers in the biomedical community have introduced deep learning-based epileptic seizure prediction models using electroencephalograms (EEGs) that can anticipate an epileptic seizure by differentiating between the pre-ictal and interic...

Interpretable Classification of Bacterial Raman Spectra With Knockoff Wavelets.

IEEE journal of biomedical and health informatics
Deep neural networks and other machine learning models are widely applied to biomedical signal data because they can detect complex patterns and compute accurate predictions. However, the difficulty of interpreting such models is a limitation, especi...

Self-Attention-Based Deep Learning Network for Regional Influenza Forecasting.

IEEE journal of biomedical and health informatics
Early prediction of influenza plays an important role in minimizing the damage caused, as it provides the resources and time needed to formulate preventive measures. Compared to traditional mechanistic approach, deep/machine learning-based models hav...

End-to-End Automatic Morphological Classification of Intracranial Pressure Pulse Waveforms Using Deep Learning.

IEEE journal of biomedical and health informatics
OBJECTIVE: Mean intracranial pressure (ICP) is commonly used in the management of patients with intracranial pathologies. However, the shape of the ICP signal over a single cardiac cycle, called ICP pulse waveform, also contains information on the st...

Establishment and External Validation of a Hypoxia-Derived Gene Signature for Robustly Predicting Prognosis and Therapeutic Responses in Glioblastoma Multiforme.

BioMed research international
OBJECTIVE: Hypoxia presents a salient feature investigated in most solid tumors that holds key roles in cancer progression, including glioblastoma multiforme (GBM). Here, we aimed to construct a hypoxia-derived gene signature for identifying the high...