AIMC Topic: Humans

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Brain-inspired multimodal hybrid neural network for robot place recognition.

Science robotics
Place recognition is an essential spatial intelligence capability for robots to understand and navigate the world. However, recognizing places in natural environments remains a challenging task for robots because of resource limitations and changing ...

Automated Placement of Scan and Pre-Scan Volumes for Breast MRI Using a Convolutional Neural Network.

Tomography (Ann Arbor, Mich.)
Graphically prescribed patient-specific imaging volumes and local pre-scan volumes are routinely placed by MRI technologists to optimize image quality. However, manual placement of these volumes by MR technologists is time-consuming, tedious, and sub...

Confidence-based laboratory test reduction recommendation algorithm.

BMC medical informatics and decision making
BACKGROUND: We propose a new deep learning model to identify unnecessary hemoglobin (Hgb) tests for patients admitted to the hospital, which can help reduce health risks and healthcare costs.

Automated approach for quality assessment of RDF resources.

BMC medical informatics and decision making
INTRODUCTION: The Semantic Web community provides a common Resource Description Framework (RDF) that allows representation of resources such that they can be linked. To maximize the potential of linked data - machine-actionable interlinked resources ...

Diagnostic performance of deep learning in infectious keratitis: a systematic review and meta-analysis protocol.

BMJ open
INTRODUCTION: Infectious keratitis (IK) represents the fifth-leading cause of blindness worldwide. A delay in diagnosis is often a major factor in progression to irreversible visual impairment and/or blindness from IK. The diagnostic challenge is fur...

Judging facts, judging norms: Training machine learning models to judge humans requires a modified approach to labeling data.

Science advances
As governments and industry turn to increased use of automated decision systems, it becomes essential to consider how closely such systems can reproduce human judgment. We identify a core potential failure, finding that annotators label objects diffe...

Large-scale electrophysiology and deep learning reveal distorted neural signal dynamics after hearing loss.

eLife
Listeners with hearing loss often struggle to understand speech in noise, even with a hearing aid. To better understand the auditory processing deficits that underlie this problem, we made large-scale brain recordings from gerbils, a common animal mo...

Deep learning models challenge the prevailing assumption that face-like effects for objects of expertise support domain-general mechanisms.

Proceedings. Biological sciences
The question of whether task performance is best achieved by domain-specific, or domain-general processing mechanisms is fundemental for both artificial and biological systems. This question has generated a fierce debate in the study of expert object...

In-Sensor Artificial Intelligence and Fusion With Electronic Medical Records for At-Home Monitoring.

IEEE transactions on biomedical circuits and systems
This work presents an artificial intelligence (AI) framework for real-time, personalized sepsis prediction four hours before onset through fusion of electrocardiogram (ECG) and patient electronic medical record. An on-chip classifier combines analog ...