AIMC Topic: Humans

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Pivotal Evaluation of an Artificial Intelligence System for Autonomous Detection of Referrable and Vision-Threatening Diabetic Retinopathy.

JAMA network open
IMPORTANCE: Diabetic retinopathy (DR) is a leading cause of blindness in adults worldwide. Early detection and intervention can prevent blindness; however, many patients do not receive their recommended annual diabetic eye examinations, primarily owi...

Drain Structural Defect Detection and Mapping Using AI-Enabled Reconfigurable Robot Raptor and IoRT Framework.

Sensors (Basel, Switzerland)
Human visual inspection of drains is laborious, time-consuming, and prone to accidents. This work presents an AI-enabled robot-assisted remote drain inspection and mapping framework using our in-house developed reconfigurable robot Raptor. The four-l...

Human Activity Recognition: A Dynamic Inductive Bias Selection Perspective.

Sensors (Basel, Switzerland)
In this article, we study activity recognition in the context of sensor-rich environments. In these environments, many different constraints arise at various levels during the data generation process, such as the intrinsic characteristics of the sens...

Deep-learning single-shot detector for automatic detection of brain metastases with the combined use of contrast-enhanced and non-enhanced computed tomography images.

European journal of radiology
PURPOSE: To develop a deep-learning object detection model for automatic detection of brain metastases that simultaneously uses contrast-enhanced and non-enhanced images as inputs, and to compare its performance with that of a model that uses only co...

MISpheroID: a knowledgebase and transparency tool for minimum information in spheroid identity.

Nature methods
Spheroids are three-dimensional cellular models with widespread basic and translational application across academia and industry. However, methodological transparency and guidelines for spheroid research have not yet been established. The MISpheroID ...

Estimating the COVID-19 prevalence and mortality using a novel data-driven hybrid model based on ensemble empirical mode decomposition.

Scientific reports
In this study, we proposed a new data-driven hybrid technique by integrating an ensemble empirical mode decomposition (EEMD), an autoregressive integrated moving average (ARIMA), with a nonlinear autoregressive artificial neural network (NARANN), cal...

A neural network for glomerulus classification based on histological images of kidney biopsy.

BMC medical informatics and decision making
BACKGROUND: Computer-aided diagnosis (CAD) systems based on medical images could support physicians in the decision-making process. During the last decades, researchers have proposed CAD systems in several medical domains achieving promising results....

Interpretable Diagnosis for Whole-Slide Melanoma Histology Images Using Convolutional Neural Network.

Journal of healthcare engineering
At present, deep learning-based medical image diagnosis had achieved high performance in several diseases. However, the black-box nature of the convolutional neural network (CNN) limits their role in diagnosis. In this study, a novel interpretable di...

A Machine-Learning-Based System for Prediction of Cardiovascular and Chronic Respiratory Diseases.

Journal of healthcare engineering
Cardiovascular and chronic respiratory diseases are global threats to public health and cause approximately 19 million deaths worldwide annually. This high mortality rate can be reduced with the use of technological advancements in medical science th...