AIMC Topic: Deep Learning

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Modelling of ecological status of Polish lakes using deep learning techniques.

Environmental science and pollution research international
Since 2000, after the Water Framework Directive came into force, aquatic ecosystems' bioassessment has acquired immense practical importance for water management. Currently, due to extensive scientific research and monitoring, we have gathered compre...

Combining Deep Learning With Optical Coherence Tomography Imaging to Determine Scalp Hair and Follicle Counts.

Lasers in surgery and medicine
BACKGROUND AND OBJECTIVES: One of the challenges in developing effective hair loss therapies is the lack of reliable methods to monitor treatment response or alopecia progression. In this study, we propose the use of optical coherence tomography (OCT...

Pollen analysis using multispectral imaging flow cytometry and deep learning.

The New phytologist
Pollen identification and quantification are crucial but challenging tasks in addressing a variety of evolutionary and ecological questions (pollination, paleobotany), but also for other fields of research (e.g. allergology, honey analysis or forensi...

A deep learning solution to recommend laboratory reduction strategies in ICU.

International journal of medical informatics
OBJECTIVE: To build a machine-learning model that predicts laboratory test results and provides a promising lab test reduction strategy, using spatial-temporal correlations.

Performance of a Deep Learning Algorithm Compared with Radiologic Interpretation for Lung Cancer Detection on Chest Radiographs in a Health Screening Population.

Radiology
Background The performance of a deep learning algorithm for lung cancer detection on chest radiographs in a health screening population is unknown. Purpose To validate a commercially available deep learning algorithm for lung cancer detection on ches...

Artificial intelligence in detection and segmentation of internal auditory canal and its nerves using deep learning techniques.

International journal of computer assisted radiology and surgery
PURPOSE: Artificial intelligence (AI) in medical imaging is a burgeoning topic that involves the interpretation of complex image structures. The recent advancements in deep learning techniques increase the computational powers to extract vital featur...

Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation.

The Lancet. Digital health
BACKGROUND: Prompt identification of patients suspected to have COVID-19 is crucial for disease control. We aimed to develop a deep learning algorithm on the basis of chest CT for rapid triaging in fever clinics.

Unveiling COVID-19 from CHEST X-Ray with Deep Learning: A Hurdles Race with Small Data.

International journal of environmental research and public health
The possibility to use widespread and simple chest X-ray (CXR) imaging for early screening of COVID-19 patients is attracting much interest from both the clinical and the AI community. In this study we provide insights and also raise warnings on what...