Prevention of medical errors

Critiquing the Reasons for Making Artificial Moral Agents.

Many industry leaders and academics from the field of machine ethics would have us believe that the inevitability of robots coming to have a larger role in our lives demands that robots be endowed with moral reasoning capabilities. Robots endowed in this way may be referred to as artificial moral agents (AMA). Reasons often given for developing AMAs are: the prevention of harm, the necessity for p...

Prediction of inherited genomic susceptibility to 20 common cancer types by a supervised machine-learning method.

Prevention and early intervention are the most effective ways of avoiding or minimizing psychological, physical, and financial suffering from cancer. However, such proactive action requires the ability to predict the individual's susceptibility to cancer with a measure of probability. Of the triad of cancer-causing factors (inherited genomic susceptibility, environmental factors, and lifestyle fac...

Fully automatic cervical vertebrae segmentation framework for X-ray images.

The cervical spine is a highly flexible anatomy and therefore vulnerable to injuries. Unfortunately, a large number of injuries in lateral cervical X-...

Risk factors for predicting increased surgical drain output in patients after anterior cervical corpectomy and fusion.

BACKGROUND: Although measures to reduce and treat the postoperative surgical drain output are discussed, along with the increased interest in causativ...

Automatic schizophrenic discrimination on fNIRS by using complex brain network analysis and SVM.

BACKGROUND: Schizophrenia is a kind of serious mental illness. Due to the lack of an objective physiological data supporting and a unified data analys...

Forecasting influenza-like illness dynamics for military populations using neural networks and social media.

This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals...

Medication discrepancies in late-stage chronic kidney disease.

BACKGROUND: Late-stage chronic kidney disease (LS-CKD) can be defined by glomerular filtration rate (GFR) 0-30 mL/min. It is a period of risk for medi...

Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network.

BACKGROUND: Ocular images play an essential role in ophthalmological diagnoses. Having an imbalanced dataset is an inevitable issue in automated ocula...

Rapid and accurate intraoperative pathological diagnosis by artificial intelligence with deep learning technology.

Frozen section is widely used for intraoperative pathological diagnosis (IOPD), which is essential for intraoperative decision making. However, frozen...

Spiking Neural P Systems with Communication on Request.

Spiking Neural [Formula: see text] Systems are Neural System models characterized by the fact that each neuron mimics a biological cell and the commun...

Evaluation of a companion robot based on field tests with single older adults in their homes.

The growing number of older adults places insurmountable load on family members and professional caregivers. Assistive technology with the aid of robo...

Omics Data Complementarity Underlines Functional Cross-Communication in Yeast.

Mapping the complete functional layout of a cell and understanding the cross-talk between different processes are fundamental challenges. They elude u...

Emergence of ultrafast sparsely synchronized rhythms and their responses to external stimuli in an inhomogeneous small-world complex neuronal network.

We consider an inhomogeneous small-world network (SWN) composed of inhibitory short-range (SR) and long-range (LR) interneurons, and investigate the e...

Prediction of crime occurrence from multi-modal data using deep learning.

In recent years, various studies have been conducted on the prediction of crime occurrences. This predictive capability is intended to assist in crime...

Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer.

Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for patients with cancer. Yet, inter-pathologist variability i...

A bio-inspired electrocommunication system for small underwater robots.

Weakly electric fishes (Gymnotid and Mormyrid) use an electric field to communicate efficiently (termed electrocommunication) in the turbid waters of ...

Improving therapeutic outcomes in autism spectrum disorders: Enhancing social communication and sensory processing through the use of interactive robots.

For children with autism spectrum disorders (ASDs), social robots are increasingly utilized as therapeutic tools in order to enhance social skills and...

Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network.

Tuberculosis (TB) affects people globally and is being reconsidered as a serious public health problem in China. Reliable forecasting is useful for th...

Twitter Influenza Surveillance: Quantifying Seasonal Misdiagnosis Patterns and their Impact on Surveillance Estimates.

BACKGROUND: Influenza (flu) surveillance using Twitter data can potentially save lives and increase efficiency by providing governments and healthcare...

Efficacy of tildipirosin metaphylaxis for the prevention of respiratory disease, otitis and mortality in pre-weaned Holstein calves.

The aim of this study was to evaluate the efficacy of two metaphylactic approaches (long acting antibiotic injected once at 10 days of life or twice a...