AIMC Topic: Humans

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[Artificial Intelligence for the Development of Screening Parameters in the Field of Corneal Biomechanics].

Klinische Monatsblatter fur Augenheilkunde
Machine learning and artificial intelligence are mostly important if data analysis by knowledge-based analytical methods is difficult and complex. In such cases, combined analytical and empirical approaches based on AI are also meaningful. The develo...

Reconstruction error based deep neural networks for coronary heart disease risk prediction.

PloS one
Coronary heart disease (CHD) is one of the leading causes of death worldwide; if suffering from CHD and being in its end-stage, the most advanced treatments are required, such as heart surgery and heart transplant. Moreover, it is not easy to diagnos...

Orbit image analysis machine learning software can be used for the histological quantification of acute ischemic stroke blood clots.

PloS one
Our aim was to assess the utility of a novel machine learning software (Orbit Image Analysis) in the histological quantification of acute ischemic stroke (AIS) clots. We analyzed 50 AIS blood clots retrieved using mechanical thrombectomy procedures. ...

Prediction of hospital no-show appointments through artificial intelligence algorithms.

Annals of Saudi medicine
BACKGROUND: No-shows, a major issue for healthcare centers, can be quite costly and disruptive. Capacity is wasted and expensive resources are underutilized. Numerous studies have shown that reducing uncancelled missed appointments can have a tremend...

Design and Integration of a Parallel, Soft Robotic End-Effector for Extracorporeal Ultrasound.

IEEE transactions on bio-medical engineering
OBJECTIVE: In this work we address limitations in state-of-the-art ultrasound robots by designing and integrating a novel soft robotic system for ultrasound imaging. It employs the inherent qualities of soft fluidic actuators to establish safe, adapt...

Utilizing wavelet deep learning network to classify different states of task-fMRI for verifying activation regions.

The International journal of neuroscience
We propose a convolutional neural network (CNN) based on wavelet for verifying the activation regions decided with statistical analysis. Because the functional magnetic resonance imaging (fMRI) data contains lots of noises, it is difficult to get th...

Rethinking drug design in the artificial intelligence era.

Nature reviews. Drug discovery
Artificial intelligence (AI) tools are increasingly being applied in drug discovery. While some protagonists point to vast opportunities potentially offered by such tools, others remain sceptical, waiting for a clear impact to be shown in drug discov...

Automated oral squamous cell carcinoma identification using shape, texture and color features of whole image strips.

Tissue & cell
Despite profound knowledge of the incidence of oral cancers and a large body of research beyond it, it continues to beat diagnosis and treatment management. Post physical observation by clinicians, a biopsy is a gold standard for accurate detection o...

Skin lesion segmentation using high-resolution convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Skin lesion segmentation is an important but challenging task in computer-aided diagnosis of dermoscopy images. Many segmentation methods based on convolutional neural networks often fail to extract accurate lesion boundarie...

Soft detection of 5-day BOD with sparse matrix in city harbor water using deep learning techniques.

Water research
To better control and manage harbor water quality is an important mission for coastal cities such as New York City (NYC). To achieve this, managers and governors need keep track of key quality indicators, such as temperature, pH, and dissolved oxygen...