AIMC Topic: Humans

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The concepts of muscle activity generation driven by upper limb kinematics.

Biomedical engineering online
BACKGROUND: The underlying motivation of this work is to demonstrate that artificial muscle activity of known and unknown motion can be generated based on motion parameters, such as angular position, acceleration, and velocity of each joint (or the e...

Intelligent solution predictive networks for non-linear tumor-immune delayed model.

Computer methods in biomechanics and biomedical engineering
In this article, we analyze the dynamics of the non-linear tumor-immune delayed (TID) model illustrating the interaction among tumor cells and the immune system (cytotoxic T lymphocytes, T helper cells), where the delays portray the times required fo...

Robot-assisted percutaneous pedicle screw placement accuracy compared with alternative guidance in lateral single-position surgery: a systematic review and meta-analysis.

Journal of neurosurgery. Spine
OBJECTIVE: While single-position surgery (SPS) eliminates the need for patient repositioning, the placement of screws in the unconventional lateral position poses unique challenges related to asymmetry relative to the surgical table. Use of robotic g...

Quantitative phase imaging of living red blood cells combining digital holographic microscopy and deep learning.

Journal of biophotonics
Digital holographic microscopy as a non-contacting, non-invasive, and highly accurate measurement technology, is becoming a valuable method for quantitatively investigating cells and tissues. Reconstruction of phases from a digital hologram is a key ...

Transcriptional intra-tumour heterogeneity predicted by deep learning in routine breast histopathology slides provides independent prognostic information.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Intra-tumour heterogeneity (ITH) causes diagnostic challenges and increases the risk for disease recurrence. Quantification of ITH is challenging and has not been demonstrated in large studies. It has previously been shown that deep learn...

Development of a Deep Learning-Based System for Optic Nerve Characterization in Transorbital Ultrasound Images on a Multicenter Data Set.

Ultrasound in medicine & biology
OBJECTIVE: Characterization of the optic nerve through measurement of optic nerve diameter (OND) and optic nerve sheath diameter (ONSD) using transorbital sonography (TOS) has proven to be a useful tool for the evaluation of intracranial pressure (IC...

Using a deep learning neural network for the identification of malignant cells in effusion cytology material.

Cytopathology : official journal of the British Society for Clinical Cytology
AIM: To evaluate the application of an artificial neural network in the detection of malignant cells in effusion samples.

Listening and responsiveness in getting-acquainted processes.

Current opinion in psychology
Listening and being responsive to another's turns at disclosure are essential processes that occur at all stages of a relationship, including and perhaps particularly at the formation stage. This article discusses research on the role of responsivene...

Unveiling the benefits of multitasking in disentangled representation formation.

Trends in cognitive sciences
Johnston and Fusi recently investigated the emergence of disentangled representations when a neural network was trained to perform multiple simultaneous tasks. Such experiments explore the benefits of flexible representations and add to a growing fie...

The human cost of ethical artificial intelligence.

Brain structure & function
Foundational models such as ChatGPT critically depend on vast data scales the internet uniquely enables. This implies exposure to material varying widely in logical sense, factual fidelity, moral value, and even legal status. Whereas data scaling is ...