AIMC Topic: Deep Learning

Clear Filters Showing 16601 to 16610 of 28423 articles

Enhancement of Patient Facial Recognition through Deep Learning Algorithm: ConvNet.

Journal of healthcare engineering
The use of machine learning algorithms for facial expression recognition and patient monitoring is a growing area of research interest. In this study, we present a technique for facial expression recognition based on deep learning algorithm: convolut...

A Computer-Aided Diagnosis System Using Deep Learning for Multiclass Skin Lesion Classification.

Computational intelligence and neuroscience
In the USA, each year, almost 5.4 million people are diagnosed with skin cancer. Melanoma is one of the most dangerous types of skin cancer, and its survival rate is 5%. The development of skin cancer has risen over the last couple of years. Early id...

Abdominal computed tomography localizer image generation: A deep learning approach.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Computed Tomography (CT) has become an important clinical imaging modality, as well as the leading source of radiation dose from medical imaging procedures. Modern CT exams are usually led by two quick orthogonal localizatio...

Implementation and Practice of Deep Learning-Based Instance Segmentation Algorithm for Quantification of Hepatic Fibrosis at Whole Slide Level in Sprague-Dawley Rats.

Toxicologic pathology
Exponential development in artificial intelligence or deep learning technology has resulted in more trials to systematically determine the pathological diagnoses using whole slide images (WSIs) in clinical and nonclinical studies. In this study, we a...

AI ethics in computational psychiatry: From the neuroscience of consciousness to the ethics of consciousness.

Behavioural brain research
Methods used in artificial intelligence (AI) overlap with methods used in computational psychiatry (CP). Hence, considerations from AI ethics are also relevant to ethical discussions of CP. Ethical issues include, among others, fairness and data owne...

LectinOracle: A Generalizable Deep Learning Model for Lectin-Glycan Binding Prediction.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Ranging from bacterial cell adhesion over viral cell entry to human innate immunity, glycan-binding proteins or lectins are abound in nature. Widely used as staining and characterization reagents in cell biology and crucial for understanding the inte...

Deep learning-based artificial intelligence applications in prostate MRI: brief summary.

The British journal of radiology
Prostate cancer (PCa) is the most common cancer type in males in the Western World. MRI has an established role in diagnosis of PCa through guiding biopsies. Due to multistep complex nature of the MRI-guided PCa diagnosis pathway, diagnostic performa...

DeepRank: a deep learning framework for data mining 3D protein-protein interfaces.

Nature communications
Three-dimensional (3D) structures of protein complexes provide fundamental information to decipher biological processes at the molecular scale. The vast amount of experimentally and computationally resolved protein-protein interfaces (PPIs) offers th...

A deep learning framework identifies dimensional representations of Alzheimer's Disease from brain structure.

Nature communications
Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a semi-supervised deep-clustering method, which examines neuroanatomical...

Deep learning based MRI contrast synthesis using full volume prediction using full volume prediction.

Biomedical physics & engineering express
In Magnetic Resonance Imaging (MRI), depending on the image acquisition settings, a large number of image types or contrasts can be generated showing complementary information of the same imaged subject. This multi-spectral information is highly bene...