AIMC Topic: Female

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People are averse to machines making moral decisions.

Cognition
Do people want autonomous machines making moral decisions? Nine studies suggest that that the answer is 'no'-in part because machines lack a complete mind. Studies 1-6 find that people are averse to machines making morally-relevant driving, legal, me...

Building a knowledge base: Predicting self-derivation through integration in 6- to 10-year-olds.

Journal of experimental child psychology
Self-derivation of new factual knowledge through integration of separate episodes of learning is one means by which children build knowledge. Content generated in this manner becomes incorporated into the knowledge base and is retained over time; suc...

Clinical prediction of HBV and HCV related hepatic fibrosis using machine learning.

EBioMedicine
Clinical prediction of advanced hepatic fibrosis (HF) and cirrhosis has long been challenging due to the gold standard, liver biopsy, being an invasive approach with certain limitations. Less invasive blood test tandem with a cutting-edge machine lea...

Deep learning applied to whole-brain connectome to determine seizure control after epilepsy surgery.

Epilepsia
OBJECTIVE: We evaluated whether deep learning applied to whole-brain presurgical structural connectomes could be used to predict postoperative seizure outcome more accurately than inference from clinical variables in patients with mesial temporal lob...

Synbiotic meal decreases uremic toxins in hemodialysis individuals: A placebo-controlled trial.

Food research international (Ottawa, Ont.)
Generation of uremic toxins p-cresylsulfate (p-CS), indoxyl sulfate (IS) and indole 3-acetic acid (IAA) in hemodialysis (HD) individuals may be associated with the gut flora and recognized markers of disease progression. This study investigated the e...

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.

NeuroImage
The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is importan...

Transfer learning with deep convolutional neural network for liver steatosis assessment in ultrasound images.

International journal of computer assisted radiology and surgery
PURPOSE: The nonalcoholic fatty liver disease is the most common liver abnormality. Up to date, liver biopsy is the reference standard for direct liver steatosis quantification in hepatic tissue samples. In this paper we propose a neural network-base...

Activity-aware essential tremor evaluation using deep learning method based on acceleration data.

Parkinsonism & related disorders
BACKGROUND: Essential tremor (ET), one of the most common neurological disorders is typically evaluated with validated rating scales which only provide a subjective assessment during a clinical visit, underestimating the fluctuations tremor during di...

Development of Machine Learning Algorithms for Prediction of 5-Year Spinal Chordoma Survival.

World neurosurgery
BACKGROUND: Chordomas are locally invasive slow-growing tumors that are difficult to study because of the rarity of the tumors and the lack of significant volumes of patients with longitudinal follow-up. As such, there are currently no machine learni...