AIMC Topic: Humans

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Automated semantic labeling of pediatric musculoskeletal radiographs using deep learning.

Pediatric radiology
BACKGROUND: An automated method for identifying the anatomical region of an image independent of metadata labels could improve radiologist workflow (e.g., automated hanging protocols) and help facilitate the automated curation of large medical imagin...

Incorporated region detection and classification using deep convolutional networks for bone age assessment.

Artificial intelligence in medicine
Bone age assessment plays an important role in the endocrinology and genetic investigation of patients. In this paper, we proposed a deep learning-based approach for bone age assessment by integration of the Tanner-Whitehouse (TW3) methods and deep c...

Automatic segmentation of Sperm's parts in microscopic images of human semen smears using concatenated learning approaches.

Computers in biology and medicine
Accurate segmentation of the sperms in microscopic semen smear images is a prerequisite step in automatic sperm morphology analysis. It is a challenging task due to the non-uniform distribution of light in semen smear images, low contrast between spe...

Gaussian Process Trajectory Learning and Synthesis of Individualized Gait Motions.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper proposes a Gaussian process-based method for trajectory learning and generation of individualized gait motions at arbitrary user-designated walking speeds, intended to be used in generating reference motions for robotic gait rehabilitation...

Deep Learning for Diagnosis of Chronic Myocardial Infarction on Nonenhanced Cardiac Cine MRI.

Radiology
Background Renal impairment is common in patients with coronary artery disease and, if severe, late gadolinium enhancement (LGE) imaging for myocardial infarction (MI) evaluation cannot be performed. Purpose To develop a fully automatic framework for...

Sparse support vector machines with L approximation for ultra-high dimensional omics data.

Artificial intelligence in medicine
Omics data usually have ultra-high dimension (p) and small sample size (n). Standard support vector machines (SVMs), which minimize the L norm for the primal variables, only lead to sparse solutions for the dual variables. L based SVMs, directly mini...

Streptococcus Gallolyticus endocarditis in patient with liver cirrhosis: a case report.

Journal of infection in developing countries
Streptococcus gallolyticus (S. gallolyticus) bacteremia is commonly associated with endocarditis and diseases of gastrointestinal tract, especially with colorectal carcinoma. On the other side, it is rarely connected to liver disease, especially alco...

A Mature-Tomato Detection Algorithm Using Machine Learning and Color Analysis.

Sensors (Basel, Switzerland)
An algorithm was proposed for automatic tomato detection in regular color images to reduce the influence of illumination and occlusion. In this method, the Histograms of Oriented Gradients (HOG) descriptor was used to train a Support Vector Machine (...

Predicting Academic Performance of Students Using a Hybrid Data Mining Approach.

Journal of medical systems
Data mining offers strong techniques for different sectors involving education. In the education field the research is developing rapidly increasing due to huge number of student's information which can be used to invent valuable pattern pertaining l...

Implications of asymmetric neural activity patterns in the basal ganglia outflow in the integrative neural network model for cervical dystonia.

Progress in brain research
Cervical dystonia (CD) is characterized by abnormal twisting and turning of the head with associated head oscillations. It is the most common form of dystonia, which is a third most common movement disorder. Despite frequent occurrence there is pauci...