Lymphoma

Emergence of non-artificial intelligence digital health innovations in ophthalmology: A systematic review.

The prominent rise of digital health in ophthalmology is evident in the current age of Industry 4.0....

Deep ConvNet: Non-Random Weight Initialization for Repeatable Determinism, Examined with FSGM.

A repeatable and deterministic non-random weight initialization method in convolutional layers of ne...

Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning.

Over the past years, large consortia have been established to fuel the sequencing of whole genomes o...

Instance elimination strategy for non-convex multiple-instance learning using sparse positive bags.

In some multiple instance learning (MIL) applications, positive bags are sparse (i.e. containing onl...

Rapid high-quality PET Patlak parametric image generation based on direct reconstruction and temporal nonlocal neural network.

Parametric imaging based on dynamic positron emission tomography (PET) has wide applications in neur...

A heuristic perspective on non-variational free energy modulation at the sleep-like edge.

BACKGROUND: The variational Free Energy Principle (FEP) establishes that a neural system minimizes a...

Fuzzy rank-based fusion of CNN models using Gompertz function for screening COVID-19 CT-scans.

COVID-19 has crippled the world's healthcare systems, setting back the economy and taking the lives ...

ncRDense: A novel computational approach for classification of non-coding RNA family by deep learning.

With the rapidly growing importance of biological research, non-coding RNAs (ncRNA) attract more att...

Assessment of deep learning-based PET attenuation correction frameworks in the sinogram domain.

This study set out to investigate various deep learning frameworks for PET attenuation correction in...

Machine learning liver-injuring drug interactions with non-steroidal anti-inflammatory drugs (NSAIDs) from a retrospective electronic health record (EHR) cohort.

Drug-drug interactions account for up to 30% of adverse drug reactions. Increasing prevalence of ele...

A machine learning based exploration of COVID-19 mortality risk.

Early prediction of patient mortality risks during a pandemic can decrease mortality by assuring eff...

Non-invasive thyroid detection based on electroglottogram signal using machine learning classifiers.

Thyroid is a butterfly shaped gland located in the neck region. Hormones are secreted by the thyroid...

Clinical decision support algorithm based on machine learning to assess the clinical response to anti-programmed death-1 therapy in patients with non-small-cell lung cancer.

OBJECTIVE: Anti-programmed death (PD)-1 therapy confers sustainable clinical benefits for patients w...

Deriving mechanistic insights from machine learning and its possible implications in non-invasive brain stimulation research.

Predicting lethal courses in critically ill COVID-19 patients using a machine learning model trained on patients with non-COVID-19 viral pneumonia.

In a pandemic with a novel disease, disease-specific prognosis models are available only with a dela...

Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations.

Structure prediction for proteins lacking homologous templates in the Protein Data Bank (PDB) remain...

Machine learning enhances the performance of short and long-term mortality prediction model in non-ST-segment elevation myocardial infarction.

Machine learning (ML) has been suggested to improve the performance of prediction models. Neverthele...

Machine learning differentiates enzymatic and non-enzymatic metals in proteins.

Metalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme reactions. Because...

Pixel-Level Fatigue Crack Segmentation in Large-Scale Images of Steel Structures Using an Encoder-Decoder Network.

Fatigue cracks are critical types of damage in steel structures due to repeated loads and distortion...

Valorization of groundnut shell via pyrolysis: Product distribution, thermodynamic analysis, kinetic estimation, and artificial neural network modeling.

Pyrolysis of agricultural biomass is a promising technique for producing renewable energy and effect...

3D Reconstruction of Non-Rigid Plants and Sensor Data Fusion for Agriculture Phenotyping.

Technology has been promoting a great transformation in farming. The introduction of robotics; the u...