AIMC Topic: Female

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Segmenting brain tumors from FLAIR MRI using fully convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Magnetic resonance imaging (MRI) is an indispensable tool in diagnosing brain-tumor patients. Automated tumor segmentation is being widely researched to accelerate the MRI analysis and allow clinicians to precisely plan trea...

Sex estimation using sternum part lenghts by means of artificial neural networks.

Forensic science international
In addition to the pelvis, cranium and phalanges, the sternum is also used for postmortem sex identification. Bone measurements may be obtained on cadaveric bones. Alternatively, computerized tomography may be used to obtain measurements close to the...

Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning.

Cancer medicine
To develop a deep learning system based on 3D convolutional neural networks (CNNs), and to automatically predict EGFR-mutant pulmonary adenocarcinoma in CT images. A dataset of 579 nodules with EGFR mutation status labels of mutant (Mut) or wild-type...

Effects of obesity on breast size, thoracic spine structure and function, upper torso musculoskeletal pain and physical activity in women.

Journal of sport and health science
PURPOSE: This study investigated the effects of obesity on breast size, thoracic spine structure and function, upper torso musculoskeletal pain and physical activity participation in women living independently in the community.

Detection of smoking status from retinal images; a Convolutional Neural Network study.

Scientific reports
Cardiovascular diseases are directly linked to smoking habits, which has both physiological and anatomical effects on the systemic and retinal circulations, and these changes can be detected with fundus photographs. Here, we aimed to 1- design a Conv...

Classifying intracranial stenosis disease severity from functional MRI data using machine learning.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Translation of many non-invasive hemodynamic MRI methods to cerebrovascular disease patients has been hampered by well-known artifacts associated with delayed blood arrival times and reduced microvascular compliance. Using machine learning and suppor...

Classification of cow milk using artificial neural network developed from the spectral data of single- and three-detector spectrophotometers.

Food chemistry
Spectra data from two instruments (UV-Vis/NIR and FT-NIR) consisting of three and one detectors, respectively, were employed in order to discriminate the geographical origin of milk as a way to detect adulteration. Initially, principal component anal...

Classification for invasion depth of esophageal squamous cell carcinoma using a deep neural network compared with experienced endoscopists.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Cancer invasion depth is a critical factor affecting the choice of treatment in patients with superficial squamous cell carcinoma (SCC). However, the diagnosis of invasion depth is currently subjective and liable to interobserver...

A RR interval based automated apnea detection approach using residual network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Apnea is one of the most common conditions that causes sleep-disorder breathing. With growing number of patients worldwide, more and more patients suffer from complications of apnea. But most of them stay untreated due to th...