Surveys

Deep learning and cancer biomarkers: recognising lead-time bias - Authors' reply.

Deep learning and cancer biomarkers: recognising lead-time bias.

Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19.

The COVID-19 pandemic is presenting a disproportionate impact on minorities in terms of infection ra...

Sharing Practices for Datasets Related to Accessibility and Aging.

Datasets sourced from people with disabilities and older adults play an important role in innovation...

Brief Survey on Machine Learning in Epistasis.

In biology, the term "epistasis" indicates the effect of the interaction of a gene with another gene...

Rethinking the Approach to Artificial Intelligence for Medical Image Analysis: The Case for Precision Diagnosis.

To date, widely generalizable artificial intelligence (AI) programs for medical image analysis have ...

Denoising Medical Images Using Machine Learning, Deep Learning Approaches: A Survey.

OBJECTIVE: Several denoising methods for medical images have been applied, such as Wavelet Transform...

NEURO-LEARN: a Solution for Collaborative Pattern Analysis of Neuroimaging Data.

The development of neuroimaging instrumentation has boosted neuroscience researches. Consequently, b...

A Survey on Machine Learning and Deep Learning-based Computer-Aided Methods for Detection of Polyps in CT Colonography.

BACKGROUND: Colon cancer generally begins as a neoplastic growth of tissue, called polyps, originati...

Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning.

Accumulating evidence demonstrates the impact of bias that reflects social inequality on the perform...

Latent bias and the implementation of artificial intelligence in medicine.

Increasing recognition of biases in artificial intelligence (AI) algorithms has motivated the quest ...

[Artificial intelligence systems and precision medicine: hopes and realities.].

Precision medicine (MP), using machine learning (ML) techniques of artificial intelligence (AI), ana...

Incorporating higher order thinking and deep learning in a large, lecture-based human physiology course: can we do it?

Large classes taught with didactic lectures and assessed with multiple-choice tests are commonly rep...

Biomedical named entity recognition and linking datasets: survey and our recent development.

Natural language processing (NLP) is widely applied in biological domains to retrieve information fr...

The emergence of new trends in clinical laboratory diagnosis.

Diagnostic processes typically rely on traditional and laborious methods, that are prone to human er...

Multidrone aerial surveys of penguin colonies in Antarctica.

Speed is essential in wildlife surveys due to the dynamic movement of animals throughout their envir...

Low-Shot Deep Learning of Diabetic Retinopathy With Potential Applications to Address Artificial Intelligence Bias in Retinal Diagnostics and Rare Ophthalmic Diseases.

IMPORTANCE: Recent studies have demonstrated the successful application of artificial intelligence (...

COVID-19 and the epistemology of epidemiological models at the dawn of AI.

The models used to estimate disease transmission, susceptibility and severity determine what epidemi...

AI on a chip.

Artificial intelligence (AI) has dramatically changed the landscape of science, industry, defence, a...

Segmentation of Masses on Mammograms Using Data Augmentation and Deep Learning.

The diagnosis of breast cancer in early stage is essential for successful treatment. Detection can b...

Estimating Reliability of Signal Quality of Physiological Data from Data Statistics Itself for Real-time Wearables.

Artificial intelligence (AI) algorithms including machine and deep learning relies on proper data fo...