Recent advances in theoretical biology suggest that key definitions of basal cognition and sentient behavior may arise as emergent properties of in vitro cell cultures and neuronal networks. Such neuronal networks reorganize activity to demonstrate s...
The rapid integration of machine learning (ML) predictors into in silico medicine has revolutionized the estimation of quantities of interest that are otherwise challenging to measure directly. However, the credibility of these predictors is critical...
Support vector machine (SVM) is one of the most popular classification algorithms in the machine learning literature. We demonstrate that SVM can be used to balance covariates and estimate average causal effects under the unconfoundedness assumption....
How episodic memories are formed in the brain is a continuing puzzle for the neuroscience community. The brain areas that are critical for episodic learning (e.g., the hippocampus) are characterized by recurrent connectivity and generate frequent off...
INTRODUCTION: Risk prediction models are increasingly used in healthcare to aid in clinical decision-making. In most clinical contexts, model calibration (i.e., assessing the reliability of risk estimates) is critical. Data available for model develo...
The objects we perceive guide our eye movements when observing real-world dynamic scenes. Yet, gaze shifts and selective attention are critical for perceiving details and refining object boundaries. Object segmentation and gaze behavior are, however,...
The international journal of medical robotics + computer assisted surgery : MRCAS
Feb 1, 2025
BACKGROUND: This study aims to develop an active following technology of the mirror-holding arm of a bedside intelligent surgical robot that enables real-time automatic tracking of surgical instruments.
The international journal of medical robotics + computer assisted surgery : MRCAS
Feb 1, 2025
BACKGROUND: Neurosurgery demands high precision, and robotic-assisted systems are increasingly employed to enhance surgical outcomes. This study focuses on a hybrid robotic-assisted system for neurosurgery, addressing forward and inverse kinematics, ...
Machine learning (ML) has shown great potential in the adaptive immune receptor repertoire (AIRR) field. However, there is a lack of large-scale ground-truth experimental AIRR data suitable for AIRR-ML-based disease diagnostics and therapeutics disco...
Heterogeneous treatment effect estimation is an important problem in precision medicine. Specific interests lie in identifying the differential effect of different treatments based on some external covariates. We propose a novel non-parametric treatm...
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