AIMC Topic: Humans

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Prediction based on machine learning of tooth sensitivity for in-office dental bleaching.

Journal of dentistry
OBJECTIVE: To develop a supervised machine learning model to predict the occurrence and intensity of tooth sensitivity (TS) in patients undergoing in-office dental bleaching testing various algorithm models.

Implementing enclosed sterile integrated robotic platforms to improve cell-based screening for drug discovery.

SLAS technology
At GSK, we have implemented custom integrated robotics platforms housed in bespoke biosafety enclosures to augment our capabilities in advanced cellular screening. Here we present and discuss the impact of one such system, the Cellular Automated Scre...

Challenges and solutions of deep learning-based automated liver segmentation: A systematic review.

Computers in biology and medicine
The liver is one of the vital organs in the body. Precise liver segmentation in medical images is essential for liver disease treatment. The deep learning-based liver segmentation process faces several challenges. This research aims to analyze the ch...

Securing healthcare medical image information using advance morphological component analysis, information hiding systems, and hybrid convolutional neural networks on IoMT.

Computers in biology and medicine
Health care images contain a variety of imaging information that has specific features, which can make it challenging to assess and decide on the methods necessitated to safeguard the highly classified visuals from unauthorized exposure during transm...

Design and validation of Withings ECG Software 2, a tiny neural network based algorithm for detection of atrial fibrillation.

Computers in biology and medicine
BACKGROUND: Atrial Fibrillation (AF) is the most common form of arrhythmia in the world with a prevalence of 1%-2%. AF is also associated with an increased risk of cardiovascular diseases (CVD), such as stroke, heart failure, and coronary artery dise...

When the bot walks the talk: Investigating the foundations of trust in an artificial intelligence (AI) chatbot.

Journal of experimental psychology. General
The concept of trust in artificial intelligence (AI) has been gaining increasing relevance for understanding and shaping human interaction with AI systems. Despite a growing literature, there are disputes as to whether the processes of trust in AI ar...

Personalized federated learning for abdominal multi-organ segmentation based on frequency domain aggregation.

Journal of applied clinical medical physics
PURPOSE: The training of deep learning (DL) models in medical images requires large amounts of sensitive patient data. However, acquiring adequately labeled datasets is challenging because of the heavy workload of manual annotations and the stringent...

Machine Learning Algorithms for Neurosurgical Preoperative Planning: A Scoping Review.

World neurosurgery
BACKGROUND AND OBJECTIVE: Preoperative neurosurgical planning is an important step in avoiding surgical complications, reducing morbidity, and improving patient safety. The incursion of machine learning (ML) in this domain has recently gained attenti...

View-symmetric representations of faces in human and artificial neural networks.

Neuropsychologia
View symmetry has been suggested to be an important intermediate representation between view-specific and view-invariant representations of faces in the human brain. Here, we compared view-symmetry in humans and a deep convolutional neural network (D...

Development and validation of a machine-learning model to predict lymph node metastasis of intrahepatic cholangiocarcinoma: A retrospective cohort study.

Bioscience trends
Lymph node metastasis in intrahepatic cholangiocarcinoma significantly impacts overall survival, emphasizing the need for a predictive model. This study involved patients who underwent curative liver resection between different time periods. Three ma...