Public Health & Policy

Ethics

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

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Comparison of robot-assisted partial nephrectomy for complex (RENAL scores ≥10) and non-complex renal tumors: A single-center experience.

OBJECTIVES: To compare functional and surgical outcomes of robot-assisted partial nephrectomy for co...

Mapping research strands of ethics of artificial intelligence in healthcare: A bibliometric and content analysis.

The growth of artificial intelligence in promoting healthcare is rapidly progressing. Notwithstandin...

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...

Ethics of AI in Pathology: Current Paradigms and Emerging Issues.

Deep learning has rapidly advanced artificial intelligence (AI) and algorithmic decision-making (ADM...

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...

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...

Classification of masked image data.

Data classification is one of the most commonly used applications of machine learning. The are many ...

Editorial: Artificial Intelligence (AI) in Clinical Medicine and the 2020 CONSORT-AI Study Guidelines.

Artificial intelligence (AI) in clinical medicine includes physical robotics and devices and virtual...

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...

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...

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...

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