AIMC Topic: Algorithms

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A Novel Method for Estimating Distances from a Robot to Humans Using Egocentric RGB Camera.

Sensors (Basel, Switzerland)
Estimating distances between people and robots plays a crucial role in understanding social Human-Robot Interaction (HRI) from an egocentric view. It is a key step if robots should engage in social interactions, and to collaborate with people as part...

Cervical Cancer Identification with Synthetic Minority Oversampling Technique and PCA Analysis using Random Forest Classifier.

Journal of medical systems
Cervical cancer is the fourth most communal malignant disease amongst women worldwide. In maximum circumstances, cervical cancer indications are not perceptible at its initial stages. There are a proportion of features that intensify the threat of em...

Beyond the hype of big data and artificial intelligence: building foundations for knowledge and wisdom.

BMC medicine
Big data, coupled with the use of advanced analytical approaches, such as artificial intelligence (AI), have the potential to improve medical outcomes and population health. Data that are routinely generated from, for example, electronic medical reco...

Identifying non-O157 Shiga toxin-producing Escherichia coli (STEC) using deep learning methods with hyperspectral microscope images.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Non-O157 Shiga toxin-producing Escherichia coli (STEC) serogroups such as O26, O45, O103, O111, O121 and O145 often cause illness to people in the United States and the conventional identification of these "Big-Six" are complex. The label-free hypers...

If machines can learn, who needs scientists?

Journal of magnetic resonance (San Diego, Calif. : 1997)
Machine learning has been used in NMR in for decades, but recent developments signal explosive growth is on the horizon. An obstacle to the application of machine learning in NMR is the relative paucity of available training data, despite the existen...

Artificial intelligence for assisting diagnostics and assessment of Parkinson's disease-A review.

Clinical neurology and neurosurgery
Artificial intelligence, specifically machine learning, has found numerous applications in computer-aided diagnostics, monitoring and management of neurodegenerative movement disorders of parkinsonian type. These tasks are not trivial due to high int...

A preliminary study of using a deep convolution neural network to generate synthesized CT images based on CBCT for adaptive radiotherapy of nasopharyngeal carcinoma.

Physics in medicine and biology
This study aims to utilize a deep convolutional neural network (DCNN) for synthesized CT image generation based on cone-beam CT (CBCT) and to apply the images to dose calculations for nasopharyngeal carcinoma (NPC). An encoder-decoder 2D U-Net neural...

Robust outcome weighted learning for optimal individualized treatment rules.

Journal of biopharmaceutical statistics
Personalized medicine has received increasing attentions among scientific communities in recent years. Because patients often have heterogenous responses to treatments, discovering individualized treatment rules (ITR) is an important component of pre...

Prediction of ATP-binding sites in membrane proteins using a two-dimensional convolutional neural network.

Journal of molecular graphics & modelling
Membrane proteins, the most important drug targets, account for around 30% of total proteins encoded by the genome of living organisms. An important role of these proteins is to bind adenosine triphosphate (ATP), facilitating crucial biological proce...