AIMC Topic: Reproducibility of Results

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Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis.

Computers in biology and medicine
BACKGROUND: When left untreated, age-related macular degeneration (AMD) is the leading cause of vision loss in people over fifty in the US. Currently it is estimated that about eight million US individuals have the intermediate stage of AMD that is o...

Implementing Machine Learning in Radiology Practice and Research.

AJR. American journal of roentgenology
OBJECTIVE: The purposes of this article are to describe concepts that radiologists should understand to evaluate machine learning projects, including common algorithms, supervised as opposed to unsupervised techniques, statistical pitfalls, and data ...

Exploring temporal information in neonatal seizures using a dynamic time warping based SVM kernel.

Computers in biology and medicine
Seizure events in newborns change in frequency, morphology, and propagation. This contextual information is explored at the classifier level in the proposed patient-independent neonatal seizure detection system. The system is based on the combination...

EXiO-A Brain-Controlled Lower Limb Exoskeleton for Rhesus Macaques.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Recent advances in the field of brain-machine interfaces (BMIs) have demonstrated enormous potential to shape the future of rehabilitation and prosthetic devices. Here, a lower-limb exoskeleton controlled by the intracortical activity of an awake beh...

Automated seizure detection using limited-channel EEG and non-linear dimension reduction.

Computers in biology and medicine
Electroencephalography (EEG) is an essential component in evaluation of epilepsy. However, full-channel EEG signals recorded from 18 to 23 electrodes on the scalp is neither wearable nor computationally effective. This paper presents advantages of bo...

Dermatologist-level classification of skin cancer with deep neural networks.

Nature
Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of ski...

Deep ensemble learning of sparse regression models for brain disease diagnosis.

Medical image analysis
Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effecti...

An Integrated Soft Computing Approach to Hughes Syndrome Risk Assessment.

Journal of medical systems
The AntiPhospholipid Syndrome (APS) is an acquired autoimmune disorder induced by high levels of antiphospholipid antibodies that cause arterial and veins thrombosis, as well as pregnancy-related complications and morbidity, as clinical manifestation...

Analysis of specific serum markers of colon carcinoma using a Bhattacharyya-based support vector machine.

Genetics and molecular research : GMR
We aimed to evaluate the specificity of 12 tumor markers related to colon carcinoma and identify the most sensitive index. Bhattacharyya distance was used to evaluate the index. Then, different index combinations were used to establish a support vect...

Gap-free segmentation of vascular networks with automatic image processing pipeline.

Computers in biology and medicine
Current image processing techniques capture large vessels reliably but often fail to preserve connectivity in bifurcations and small vessels. Imaging artifacts and noise can create gaps and discontinuity of intensity that hinders segmentation of vasc...