.... 2024 Amyotrophic lateral sclerosis Facial expression Facial action units Machine learning Logistic regression Amyotrophic lateral sclerosis (ALS) is a highly dilapidating motor neuron disease. It is characterized by progressive muscle weakness and the inability to perform voluntary...

... extraction methods combined with machine learning algorithms were then used to produce a gender and language-specific (English and French) digital vocal biomarker to differentiate smokers from never-smokers. Results: A total of 1,332‬ participants were included after propensity score matching (mean age...

... in postoperative ACDF patients. We have developed and validated a machine learning neck motion classification algorithm to differentiate between eight neck motions (right/left rotation, right/left lateral bending, flexion, extension, retraction, protraction) in healthy normal subjects and patients. Methods: Sensor...

... or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements. Digital endpoints Machine learning...

... to swallowing. An ongoing challenge with this approach is consolidating these complex signals into sensitive, clinically meaningful metrics of swallowing performance. To address this gap, we propose 2 novel, digital monitoring tools to evaluate swallows using wearable sensor data and machine learning. Methods...

... prove to be a less resource-intensive medium that yields continuous and rich data on a patient’s cognition. Objective: To explore whether digital biomarkers of cognitive performance, found in the casual card game Klondike Solitaire, can be used to train machine-learning models to discern games played...

..., yet, to date, tools available to understand fatigue are severely limited. Methods: After using a recurrent neural network-based algorithm to impute missing time series data form a multisensor wearable device, we compared supervised and unsupervised machine learning approaches to gain insights...

... and accelerometer time-series data were captured. Processing schemes were developed using machine learning techniques such as logistic regression as well as explicitly programmed algorithms to assess data quality in both tasks. Motion-specific features including wrist joint range of motion (ROM) in flexion...

... that make it distinct from simply digitized versions of traditional therapeutics . Our objective is to describe a more valuable characteristic of digital therapeutics, which is distinct from traditional medicine or therapy: that is, the utilization of artificial intelligence and machine learning systems...

.... Algorithms App-based digital biomarkers Cough Digital measurement Machine learning Respiratory Cough is a common and meaningful symptom in many respiratory diseases, with both characteristic sounds and movements. Monitoring and measurement of cough in clinical trials and routine care typically...