AIMC Topic: Humans

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Deep learning to automate the labelling of head MRI datasets for computer vision applications.

European radiology
OBJECTIVES: The purpose of this study was to build a deep learning model to derive labels from neuroradiology reports and assign these to the corresponding examinations, overcoming a bottleneck to computer vision model development.

Accurate Machine-Learning-Based classification of Leukemia from Blood Smear Images.

Clinical lymphoma, myeloma & leukemia
BACKGROUND: Conventional identification of blood disorders based on visual inspection of blood smears through microscope is time consuming, error-prone and is limited by hematologist's physical acuity. Therefore, an automated optical image processing...

Automating water quality analysis using ML and auto ML techniques.

Environmental research
Generation of unprocessed effluents, municipal refuse, factory wastes, junking of compostable and non-compostable effluents has hugely contaminated nature-provided water bodies like rivers, lakes and ponds. Therefore, there is a necessity to look int...

Deep learning for sex classification in resting-state and task functional brain networks from the UK Biobank.

NeuroImage
Classification of whole-brain functional connectivity MRI data with convolutional neural networks (CNNs) has shown promise, but the complexity of these models impedes understanding of which aspects of brain activity contribute to classification. Whil...

Adoption of New Technologies: Artificial Intelligence.

Gastrointestinal endoscopy clinics of North America
Over the past decade, artificial intelligence (AI) has been broadly applied to many aspects of human life, with recent groundbreaking successes in facial recognition, natural language processing, autonomous driving, and medical imaging. Gastroenterol...

DeepCervix: A deep learning-based framework for the classification of cervical cells using hybrid deep feature fusion techniques.

Computers in biology and medicine
Cervical cancer, one of the most common fatal cancers among women, can be prevented by regular screening to detect any precancerous lesions at early stages and treat them. Pap smear test is a widely performed screening technique for early detection o...

Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours.

European journal of cancer (Oxford, England : 1990)
AIM: Sentinel lymph node status is a central prognostic factor for melanomas. However, the surgical excision involves some risks for affected patients. In this study, we therefore aimed to develop a digital biomarker that can predict lymph node metas...

The perceptions of medical physicists towards relevance and impact of artificial intelligence.

Physical and engineering sciences in medicine
Artificial intelligence (AI) is an innovative tool with the potential to impact medical physicists' clinical practices, research, and the profession. The relevance of AI and its impact on the clinical practice and routine of professionals in medical ...

Automated Annotation of Epileptiform Burden and Its Association with Outcomes.

Annals of neurology
OBJECTIVE: This study was undertaken to determine the dose-response relation between epileptiform activity burden and outcomes in acutely ill patients.

The Trifecta of Single-Cell, Systems-Biology, and Machine-Learning Approaches.

Genes
Together, single-cell technologies and systems biology have been used to investigate previously unanswerable questions in biomedicine with unparalleled detail. Despite these advances, gaps in analytical capacity remain. Machine learning, which has re...