AIMC Topic: Humans

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Deep learning for biomechanical modeling of facial tissue deformation in orthognathic surgical planning.

International journal of computer assisted radiology and surgery
PURPOSE: Orthognathic surgery requires an accurate surgical plan of how bony segments are moved and how the face passively responds to the bony movement. Currently, finite element method (FEM) is the standard for predicting facial deformation. Deep l...

Image Quality Assessment: Unifying Structure and Texture Similarity.

IEEE transactions on pattern analysis and machine intelligence
Objective measures of image quality generally operate by comparing pixels of a "degraded" image to those of the original. Relative to human observers, these measures are overly sensitive to resampling of texture regions (e.g., replacing one patch of ...

Convolutional Prototype Network for Open Set Recognition.

IEEE transactions on pattern analysis and machine intelligence
Despite the success of convolutional neural network (CNN) in conventional closed-set recognition (CSR), it still lacks robustness for dealing with unknowns (those out of known classes) in open environment. To improve the robustness of CNN in open-set...

Using artificial intelligence to support rapid, mixed-methods analysis: Developing an automated qualitative assistant (AQUA).

Annals of family medicine
Context: Qualitative research - crucial for understanding human behavior - remains underutilized, in part due to the time and cost of annotating qualitative data (coding). Artificial intelligence (AI) has been suggested as a means to reduce those bur...

Association of Open vs Robot-Assisted Radical Cystectomy With Mortality and Perioperative Outcomes Among Patients With Bladder Cancer in Sweden.

JAMA network open
IMPORTANCE: Mortality rates resulting from bladder cancer have remained unchanged for more than 30 years. The surgical community has put hope in robot-assisted radical cystectomy (RARC) with intracorporeal urinary diversion (ICUD) in an effort to imp...

AI Denoising Significantly Enhances Image Quality and Diagnostic Confidence in Interventional Cone-Beam Computed Tomography.

Tomography (Ann Arbor, Mich.)
(1) To investigate whether interventional cone-beam computed tomography (cbCT) could benefit from AI denoising, particularly with respect to patient body mass index (BMI); (2) From 1 January 2016 to 1 January 2022, 100 patients with liver-directed in...

Proof-of-Concept Analysis of a Deep Learning Model to Conduct Automated Segmentation of OCT Images for Macular Hole Volume.

Ophthalmic surgery, lasers & imaging retina
BACKGROUND AND OBJECTIVE: To determine whether an automated artificial intelligence (AI) model could assess macular hole (MH) volume on swept-source optical coherence tomography (OCT) images.

Augmented Reality for Human-Robot Collaboration and Cooperation in Industrial Applications: A Systematic Literature Review.

Sensors (Basel, Switzerland)
With the continuously growing usage of collaborative robots in industry, the need for achieving a seamless human-robot interaction has also increased, considering that it is a key factor towards reaching a more flexible, effective, and efficient prod...

Association of Selective Serotonin Reuptake Inhibitor Use With Abnormal Physical Movement Patterns as Detected Using a Piezoelectric Accelerometer and Deep Learning in a Nationally Representative Sample of Noninstitutionalized Persons in the US.

JAMA network open
IMPORTANCE: Selective serotonin reuptake inhibitors (SSRIs) are a common first-line treatment for some psychiatric disorders, including depression and anxiety; although they are generally well tolerated, SSRIs have known adverse effects, including mo...

XGB-DrugPred: computational prediction of druggable proteins using eXtreme gradient boosting and optimized features set.

Scientific reports
Accurate identification of drug-targets in human body has great significance for designing novel drugs. Compared with traditional experimental methods, prediction of drug-targets via machine learning algorithms has enhanced the attention of many rese...