AIMC Topic: Adult

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Computation noise promotes zero-shot adaptation to uncertainty during decision-making in artificial neural networks.

Science advances
Random noise in information processing systems is widely seen as detrimental to function. But despite the large trial-to-trial variability of neural activity, humans show a remarkable adaptability to conditions with uncertainty during goal-directed b...

Effect of observer's cultural background and masking condition of target face on facial expression recognition for machine-learning dataset.

PloS one
Facial expression recognition (FER) is significantly influenced by the cultural background (CB) of observers and the masking conditions of the target face. This study aimed to clarify these factors' impact on FER, particularly in machine-learning dat...

Optimizing the Prediction of Depression Remission: A Longitudinal Machine Learning Approach.

American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics
Decisions about when to change antidepressant treatment are complex and benefit from accurate prediction of treatment outcome. Prognostic accuracy can be enhanced by incorporating repeated assessments of symptom severity collected during treatment. P...

Estimating individual risk of catheter-associated urinary tract infections using explainable artificial intelligence on clinical data.

American journal of infection control
BACKGROUND: Catheter-associated urinary tract infections (CAUTIs) increase clinical burdens. Identifying the high-risk patients is crucial. We aimed to develop and externally validate an explainable, prognostic prediction model of CAUTIs among hospit...

Real-World Performance of Pneumothorax-Detecting Artificial Intelligence Algorithm and its Impact on Radiologist Reporting Times.

Academic radiology
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) algorithms in radiology capable of detecting urgent findings have gained significant traction in recent years, but the impact of these algorithms on real-world clinical practice remains unclear w...

Early prediction of radiotherapy outcomes in pharyngeal cancer using deep learning on baseline [18F]Fluorodeoxyglucose positron emission Tomography/Computed tomography.

European journal of radiology
OBJECTIVES: This study aimed to develop an integrated segmentation-free deep learning (DL) framework to predict multiple aspects of radiotherapy outcome in pharyngeal cancer patients by analyzing pretreatment 18F-fluorodeoxyglucose (18F-FDG) positron...

Seizure Sources Can Be Imaged from Scalp EEG by Means of Biophysically Constrained Deep Neural Networks.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Seizure localization is important for managing drug-resistant focal epilepsy. Here, the capability of a novel deep learning-based source imaging framework (DeepSIF) for imaging seizure activities from electroencephalogram (EEG) recordings in drug-res...

Developing a machine learning model with enhanced performance for predicting COVID-19 from patients presenting to the emergency room with acute respiratory symptoms.

IET systems biology
Artificial Intelligence is playing a crucial role in healthcare by enhancing decision-making and data analysis, particularly during the COVID-19 pandemic. This virus affects individuals across all age groups, but its impact is more severe on the elde...

Improving Pelvic Floor Muscle Training with AI: A Novel Quality Assessment System for Pelvic Floor Dysfunction.

Sensors (Basel, Switzerland)
The first line of treatment for urinary incontinence is pelvic floor muscle (PFM) training, aimed at reducing leakage episodes by strengthening these muscles. However, many women struggle with performing correct PFM contractions or have misconception...

Multi-Activity Step Counting Algorithm Using Deep Learning Foot Flat Detection with an IMU Inside the Sole of a Shoe.

Sensors (Basel, Switzerland)
Step counting devices were previously shown to be efficient in a variety of applications such as athletic training or patient's care programs. Various sensor placements and algorithms were previously experimented, with a best mean absolute percentage...