AIMC Topic: Female

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A dense multi-path decoder for tissue segmentation in histopathology images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Segmenting different tissue components in histopathological images is of great importance for analyzing tissues and tumor environments. In recent years, an encoder-decoder family of convolutional neural networks has increasi...

netDx: interpretable patient classification using integrated patient similarity networks.

Molecular systems biology
Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis, and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse da...

Visual network alterations in brain functional connectivity in chronic low back pain: A resting state functional connectivity and machine learning study.

NeuroImage. Clinical
Chronic low back pain (cLBP) is associated with widespread functional and structural changes in the brain. This study aims to investigate the resting state functional connectivity (rsFC) changes of visual networks in cLBP patients and the feasibility...

Differentiation of glioblastoma from solitary brain metastases using radiomic machine-learning classifiers.

Cancer letters
This study aimed to identify the optimal radiomic machine-learning classifier for differentiating glioblastoma (GBM) from solitary brain metastases (MET) preoperatively. Four hundred and twelve patients with solitary brain tumors (242 GBM and 170 sol...

Analysis and evaluation of handwriting in patients with Parkinson's disease using kinematic, geometrical, and non-linear features.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Parkinson's disease is a neurological disorder that affects the motor system producing lack of coordination, resting tremor, and rigidity. Impairments in handwriting are among the main symptoms of the disease. Handwriting a...

On the Relative Contribution of Deep Convolutional Neural Networks for SSVEP-Based Bio-Signal Decoding in BCI Speller Applications.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Brain-computer interfaces (BCI) harnessing steady state visual evoked potentials (SSVEPs) manipulate the frequency and phase of visual stimuli to generate predictable oscillations in neural activity. For BCI spellers, oscillations are matched with al...

Effects of Gender and Relationship Type on the Response to Artificial Intelligence.

Cyberpsychology, behavior and social networking
Artificial intelligence (AI) has had a huge impact on our lives. In this study, we suggest that when people interact with AI, they regard the AI as a social actor and apply interpersonal relationship norms. This study employed a 2 × 2 between-subject...

Predicting hospital-acquired pneumonia among schizophrenic patients: a machine learning approach.

BMC medical informatics and decision making
BACKGROUND: Medications are frequently used for treating schizophrenia, however, anti-psychotic drug use is known to lead to cases of pneumonia. The purpose of our study is to build a model for predicting hospital-acquired pneumonia among schizophren...

Convolutional neural network for cell classification using microscope images of intracellular actin networks.

PloS one
Automated cell classification is an important yet a challenging computer vision task with significant benefits to biomedicine. In recent years, there have been several studies attempted to build an artificial intelligence-based cell classifier using ...