AIMC Topic: Humans

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MD-MLI: Prediction of miRNA-lncRNA Interaction by Using Multiple Features and Hierarchical Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Long non-coding RNA(lncRNA) can interact with microRNA(miRNA) and play an important role in inhibiting or activating the expression of target genes and the occurrence and development of tumors. Accumulating studies focus on the prediction of miRNA-ln...

LDICDL: LncRNA-Disease Association Identification Based on Collaborative Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
It has been proved that long noncoding RNA (lncRNA) plays critical roles in many human diseases. Therefore, inferring associations between lncRNAs and diseases can contribute to disease diagnosis, prognosis and treatment. To overcome the limitation o...

Identification of Functional piRNAs Using a Convolutional Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
Piwi-interacting RNAs (piRNAs) are a distinct sub-class of small non-coding RNAs that are mainly responsible for germline stem cell maintenance, gene stability, and maintaining genome integrity by repression of transposable elements. piRNAs are also ...

Neuropsychological test using machine learning for cognitive impairment screening.

Applied neuropsychology. Adult
OBJECTIVES: Neuropsychological tests (NPTs) are widely used tools to evaluate cognitive functioning. The interpretation of these tests can be time-consuming and requires a specialized clinician. For this reason, we trained machine learning models tha...

Modulations of one's sense of agency during human-machine interactions: A behavioural study using a full humanoid robot.

Quarterly journal of experimental psychology (2006)
Although previous investigations reported a reduced sense of agency when individuals act with traditional machines, little is known about the mechanisms underpinning interactions with human-like automata. The aim of this study was twofold: (1) to inv...

The robotic-assisted extended "Sistrunk" approach for tumors of the upper aerodigestive tract with limited transoral access: First description of oncological and functional outcomes.

Head & neck
We report on the first clinical experience with the robotic-assisted extended "Sistrunk" approach (RESA) for access to constrained spaces of the upper aerodigestive tract. This prospective case cohort study include six patients that underwent RESA if...

Natural Language Processing for Imaging Protocol Assignment: Machine Learning for Multiclass Classification of Abdominal CT Protocols Using Indication Text Data.

Journal of digital imaging
A correct protocol assignment is critical to high-quality imaging examinations, and its automation can be amenable to natural language processing (NLP). Assigning protocols for abdominal imaging CT scans is particularly challenging given the multiple...

Effective heart disease prediction with Grey-wolf with Firefly algorithm-differential evolution (GF-DE) for feature selection and weighted ANN classification.

Computer methods in biomechanics and biomedical engineering
In recent time, heart disease has become common leading to mortality of many individuals. Hence, early and accurate prediction of this disease is vital to reduce death rate and enhance people's lives. Concurrently, Artificial Intelligence has gained ...

⊥-loss: A symmetric loss function for magnetic resonance imaging reconstruction and image registration with deep learning.

Medical image analysis
Convolutional neural networks (CNNs) are increasingly adopted in medical imaging, e.g., to reconstruct high-quality images from undersampled magnetic resonance imaging (MRI) acquisitions or estimate subject motion during an examination. MRI is natura...

Massive external validation of a machine learning algorithm to predict pulmonary embolism in hospitalized patients.

Thrombosis research
BACKGROUND: Pulmonary embolism (PE) is a life-threatening condition associated with ~10% of deaths of hospitalized patients. Machine learning algorithms (MLAs) which predict the onset of pulmonary embolism (PE) could enable earlier treatment and impr...