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Latest AI and machine learning research in surveys for healthcare professionals.

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An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare.

The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity o...

An artificial neural network approach for predicting hypertension using NHANES data.

This paper focus on a neural network classification model to estimate the association among gender, ...

Hiding a plane with a pixel: examining shape-bias in CNNs and the benefit of building in biological constraints.

When deep convolutional neural networks (CNNs) are trained "end-to-end" on raw data, some of the fea...

Machine learning for genetic prediction of psychiatric disorders: a systematic review.

Machine learning methods have been employed to make predictions in psychiatry from genotypes, with t...

Identifying the Symptom Severity in Obsessive-Compulsive Disorder for Classification and Prediction: An Artificial Neural Network Approach.

The present study is aimed at identifying the most prominent determinants of OCD along with their st...

Clinical questionnaire filling based on question answering framework.

BACKGROUND: Electronic Health Records (EHR) are the foundation of much medical research. However, an...

In AI We Trust: Ethics, Artificial Intelligence, and Reliability.

One of the main difficulties in assessing artificial intelligence (AI) is the tendency for people to...

Big-Data Science in Porous Materials: Materials Genomics and Machine Learning.

By combining metal nodes with organic linkers we can potentially synthesize millions of possible met...

MRI Segmentation and Classification of Human Brain Using Deep Learning for Diagnosis of Alzheimer's Disease: A Survey.

Many neurological diseases and delineating pathological regions have been analyzed, and the anatomic...

Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks.

Chemical representations derived from deep learning are emerging as a powerful tool in areas such as...

Big Data Driven Detection of Trees in Suburban Scenes Using Visual Spectrum Eye Level Photography.

The aim of the work described in this paper is to detect trees in eye level view images. Unlike prev...

Deep learning COVID-19 detection bias: accuracy through artificial intelligence.

BACKGROUND: Detection of COVID-19 cases' accuracy is posing a conundrum for scientists, physicians, ...

Role of biological Data Mining and Machine Learning Techniques in Detecting and Diagnosing the Novel Coronavirus (COVID-19): A Systematic Review.

Coronaviruses (CoVs) are a large family of viruses that are common in many animal species, including...

Deep learning-guided joint attenuation and scatter correction in multitracer neuroimaging studies.

PET attenuation correction (AC) on systems lacking CT/transmission scanning, such as dedicated brain...

Automated detection of the head-twitch response using wavelet scalograms and a deep convolutional neural network.

Hallucinogens induce the head-twitch response (HTR), a rapid reciprocal head movement, in mice. Alth...

Applying Machine Learning to Kinematic and Eye Movement Features of a Movement Imitation Task to Predict Autism Diagnosis.

Autism is a developmental condition currently identified by experts using observation, interview, an...

The Moral Choice Machine.

Allowing machines to choose whether to kill humans would be devastating for world peace and security...

Correlation of Measured and Estimated Creatinine Clearance in Hospitalized Elderly Patients: A Retrospective Cohort Study.

Accurate assessment of renal function is essential in hospitalized elderly patients. Few studies ha...

Static Tactile Sensing for a Robotic Electronic Skin via an Electromechanical Impedance-Based Approach.

Tactile sensing is paramount for robots operating in human-centered environments to help in understa...

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