Dermatology

Psoriasis

Latest AI and machine learning research in psoriasis for healthcare professionals.

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Dermatology Subcategories: Atopy Psoriasis
Showing 232-252 of 2,098 articles
Interrogating theoretical models of neural computation with emergent property inference.

A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures ...

Risk prediction for delayed clearance of high-dose methotrexate in pediatric hematological malignancies by machine learning.

This study aimed to establish a predictive model to identify children with hematologic malignancy at...

Discovery of novel DGAT1 inhibitors by combination of machine learning methods, pharmacophore model and 3D-QSAR model.

DGAT1 plays a crucial controlling role in triglyceride biosynthetic pathways, which makes it an attr...

An Autoencoder-Based Deep Learning Approach for Load Identification in Structural Dynamics.

In civil engineering, different machine learning algorithms have been adopted to process the huge am...

Deep HDR Hallucination for Inverse Tone Mapping.

Inverse Tone Mapping (ITM) methods attempt to reconstruct High Dynamic Range (HDR) information from ...

A marker registration method to improve joint angles computed by constrained inverse kinematics.

Accurate computation of joint angles from optical marker data using inverse kinematics methods requi...

DeepD2V: A Novel Deep Learning-Based Framework for Predicting Transcription Factor Binding Sites from Combined DNA Sequence.

Predicting in vivo protein-DNA binding sites is a challenging but pressing task in a variety of fiel...

MRI and CT bladder segmentation from classical to deep learning based approaches: Current limitations and lessons.

Precise determination and assessment of bladder cancer (BC) extent of muscle invasion involvement gu...

A Multiprocessing Scheme for PET Image Pre-Screening, Noise Reduction, Segmentation and Lesion Partitioning.

Accurate segmentation and partitioning of lesions in PET images provide computer-aided procedures an...

Estimation of tumor parameters using neural networks for inverse bioheat problem.

BACKGROUND AND OBJECTIVE: Some types of cancer cause rapid cell growth, while others cause cells to ...

Inverse identification of hyperelastic constitutive parameters of skeletal muscles via optimization of AI techniques.

Studies on the deformation characteristics and stress distribution in loaded skeletal muscles are of...

Deep Learning Analysis of Ultrasonic Guided Waves for Cortical Bone Characterization.

Ultrasonic guided waves (UGWs) propagating in the long cortical bone can be measured via the axial t...

Deep learning approach to skin layers segmentation in inflammatory dermatoses.

Monitoring skin layers with medical imaging is critical to diagnosing and treating patients with chr...

A convolutional neural network architecture for the recognition of cutaneous manifestations of COVID-19.

During the COVID-19 pandemic, dermatologists reported an array of different cutaneous manifestations...

Reconstruction of Organ Boundaries With Deep Learning in the D-Bar Method for Electrical Impedance Tomography.

OBJECTIVE: Medical electrical impedance tomography is a non-ionizing imaging modality in which low-a...

Comparative study using inverse ontology cogency and alternatives for concept recognition in the annotated National Library of Medicine database.

This paper introduces inverse ontology cogency, a concept recognition process and distance function ...

A proximal neurodynamic model for solving inverse mixed variational inequalities.

This paper proposes a proximal neurodynamic model (PNDM) for solving inverse mixed variational inequ...

Deep learning-based solvability of underdetermined inverse problems in medical imaging.

Recently, with the significant developments in deep learning techniques, solving underdetermined inv...

Branching principles of animal and plant networks identified by combining extensive data, machine learning and modelling.

Branching in vascular networks and in overall organismic form is one of the most common and ancient ...

A dual-domain deep learning-based reconstruction method for fully 3D sparse data helical CT.

Helical CT has been widely used in clinical diagnosis. In this work, we focus on a new prototype of ...

Deep learning-based inverse mapping for fluence map prediction.

We developed a fluence map prediction method that directly generates fluence maps for a given desire...

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