AIMC Topic: Female

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Predicting Autism Spectrum Disorder Using Domain-Adaptive Cross-Site Evaluation.

Neuroinformatics
The advances in neuroimaging methods reveal that resting-state functional fMRI (rs-fMRI) connectivity measures can be potential diagnostic biomarkers for autism spectrum disorder (ASD). Recent data sharing projects help us replicating the robustness ...

Artificial Neural Networking Model for the Prediction of Early Occlusion of Bilateral Plastic Stent Placement for Inoperable Hilar Cholangiocarcinoma.

Surgical laparoscopy, endoscopy & percutaneous techniques
BACKGROUND: This study aimed to determine whether the back-propagation artificial neural network (BP-ANN) model could be constructed to accurately in predicting early occlusion of bilateral plastic stent placement for inoperable hilar cholangiocarcin...

Predicting similarity judgments in intertemporal choice with machine learning.

Psychonomic bulletin & review
Similarity models of intertemporal choice are heuristics that choose based on similarity judgments of the reward amounts and time delays. Yet, we do not know how these judgments are made. Here, we use machine-learning algorithms to assess what factor...

Automated Radiology Report Summarization Using an Open-Source Natural Language Processing Pipeline.

Journal of digital imaging
Diagnostic radiologists are expected to review and assimilate findings from prior studies when constructing their overall assessment of the current study. Radiology information systems facilitate this process by presenting the radiologist with a subs...

Data-Adaptive Estimation for Double-Robust Methods in Population-Based Cancer Epidemiology: Risk Differences for Lung Cancer Mortality by Emergency Presentation.

American journal of epidemiology
In this paper, we propose a structural framework for population-based cancer epidemiology and evaluate the performance of double-robust estimators for a binary exposure in cancer mortality. We conduct numerical analyses to study the bias and efficien...

Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI.

Journal of digital imaging
Schizophrenia has been proposed to result from impairment of functional connectivity. We aimed to use machine learning to distinguish schizophrenic subjects from normal controls using a publicly available functional MRI (fMRI) data set. Global and lo...

The combined use of virtual reality and EEG to study language processing in naturalistic environments.

Behavior research methods
When we comprehend language, we often do this in rich settings where we can use many cues to understand what someone is saying. However, it has traditionally been difficult to design experiments with rich three-dimensional contexts that resemble our ...

[A Paired Case Controlled Study Comparing the Short-term Outcomes of Da Vinci RATS and VATS Approach for Non-small Cell Lung Cancer].

Zhongguo fei ai za zhi = Chinese journal of lung cancer
BACKGROUND: Da Vinci Surgical System is one of the greatest inventions of the 20th century, which represents the development direction of the precise minimally invasive surgical techniques, the aim of this study was to comparing the short-term outcom...

Identification of topological features in renal tumor microenvironment associated with patient survival.

Bioinformatics (Oxford, England)
MOTIVATION: As a highly heterogeneous disease, the progression of tumor is not only achieved by unlimited growth of the tumor cells, but also supported, stimulated, and nurtured by the microenvironment around it. However, traditional qualitative and/...