AIMC Topic: Female

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Deep learning-based detection and classification of geographic atrophy using a deep convolutional neural network classifier.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To automatically detect and classify geographic atrophy (GA) in fundus autofluorescence (FAF) images using a deep learning algorithm.

Establishment of a SVM classifier to predict recurrence of ovarian cancer.

Molecular medicine reports
Gene expression data using retrieved ovarian cancer (OC) samples were used to identify genes of interest and a support vector machine (SVM) classifier was subsequently established to predict the recurrence of OC. Three datasets (GSE17260, GSE44104 an...

A Robotic System for Adaptive Training and Function Assessment of Forelimb Retraction in Mice.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Rodent models are decisive for translational research in healthy and pathological conditions of motor function thanks to specific similarities with humans. Here, we present an upgraded version of the M-Platform, a robotic device previously designed t...

Cardiac Phase Space Tomography: A novel method of assessing coronary artery disease utilizing machine learning.

PloS one
BACKGROUND: Artificial intelligence (AI) techniques are increasingly applied to cardiovascular (CV) medicine in arenas ranging from genomics to cardiac imaging analysis. Cardiac Phase Space Tomography Analysis (cPSTA), employing machine-learned linea...

The diagnostic value of texture analysis in predicting WHO grades of meningiomas based on ADC maps: an attempt using decision tree and decision forest.

European radiology
OBJECTIVES: The preoperative prediction of the WHO grade of a meningioma is important for further treatment plans. This study aimed to assess whether texture analysis (TA) based on apparent diffusion coefficient (ADC) maps could non-invasively classi...

A machine learning-based prediction model of H3K27M mutations in brainstem gliomas using conventional MRI and clinical features.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND: H3K27M is the most frequent mutation in brainstem gliomas (BSGs), and it has great significance in the differential diagnosis, prognostic prediction and treatment strategy selection of BSGs. There has been a lack of reliable noninvasive m...

Identifying individuals with attention deficit hyperactivity disorder based on temporal variability of dynamic functional connectivity.

Scientific reports
Attention deficit hyperactivity disorder (ADHD) is a common disorder that emerges in school-age children. The diagnostic model based on neuroimaging features could be beneficial for ADHD in twofold: identifying individuals with ADHD and discovering t...

The computerized scoring algorithm for the autobiographical memory test: updates and extensions for analyzing memories of English-speaking adults.

Memory (Hove, England)
The Autobiographical Memory Test (AMT) has been central in psychopathological studies of memory dysfunctions, as reduced memory specificity or overgeneralised autobiographical memory has been recognised as a hallmark vulnerability for depression. In ...

Complexity in mood disorder diagnosis: fMRI connectivity networks predicted medication-class of response in complex patients.

Acta psychiatrica Scandinavica
OBJECTIVE: This study determined the clinical utility of an fMRI classification algorithm predicting medication-class of response in patients with challenging mood diagnoses.

PCA and deep learning based myoelectric grasping control of a prosthetic hand.

Biomedical engineering online
BACKGROUND: For the functional control of prosthetic hand, it is insufficient to obtain only the motion pattern information. As far as practicality is concerned, the control of the prosthetic hand force is indispensable. The application value of pros...