AIMC Topic: Smartphone

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BlazePose-Seq2Seq: Leveraging Regular RGB Cameras for Robust Gait Assessment.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Evaluation of human gait through smartphone-based pose estimation algorithms provides an attractive alternative to costly lab-bound instrumented assessment and offers a paradigm shift with real time gait capture for clinical assessment. Systems based...

Edge Artificial Intelligence (AI) for real-time automatic quantification of filariasis in mobile microscopy.

PLoS neglected tropical diseases
Filariasis, a neglected tropical disease caused by roundworms, is a significant public health concern in many tropical countries. Microscopic examination of blood samples can detect and differentiate parasite species, but it is time consuming and req...

Nucleic Acid Plate Culture: Label-Free and Naked-Eye-Based Digital Loop-Mediated Isothermal Amplification in Hydrogel with Machine Learning.

ACS sensors
Digital nucleic acid amplification enables the absolute quantification of single molecules. However, due to the ultrasmall reaction volume in the digital system (, short light path), most digital systems are limited to fluorescence signals, while lab...

Explainable prediction of problematic smartphone use among South Korea's children and adolescents using a Machine learning approach.

International journal of medical informatics
BACKGROUND: Korea is known for its technological prowess, has the highest smartphone ownership rate in the world at 95%, and the smallest gap in smartphone ownership between generations. Since the onset of the COVID-19 pandemic, problematic smartphon...

Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model.

Journal of affective disorders
BACKGROUND: Prior research has associated spoken language use with depression, yet studies often involve small or non-clinical samples and face challenges in the manual transcription of speech. This paper aimed to automatically identify depression-re...

Early childhood caries detection using smartphone artificial intelligence.

European archives of paediatric dentistry : official journal of the European Academy of Paediatric Dentistry

Nanozyme-induced deep learning-assisted smartphone integrated colorimetric and fluorometric dual-mode for detection of tetracycline analogs.

Analytica chimica acta
In this work, a colorimetric and fluorescent dual-mode probe controlled by NH-MIL-88 B (Fe, Ni) nanozymes was developed to visually detect tetracycline antibiotics (TCs) residues quantitatively, as well as accurately distinguish the four most widely ...

Artificial Intelligence-Enabled Stool Analysis for Lactulose Titration Assistance in Hepatic Encephalopathy Through a Smartphone Application.

The American journal of gastroenterology
INTRODUCTION: Management of hepatic encephalopathy relies on self-titration of lactulose. In this feasibility trial, we assess an artificial intelligence-enabled tool to guide lactulose use through a smartphone application.

AMDDLmodel: Android smartphones malware detection using deep learning model.

PloS one
Android is the most popular operating system of the latest mobile smart devices. With this operating system, many Android applications have been developed and become an essential part of our daily lives. Unfortunately, different kinds of Android malw...

A Review of Image-Based Food Recognition and Volume Estimation Artificial Intelligence Systems.

IEEE reviews in biomedical engineering
The daily healthy diet and balanced intake of essential nutrients play an important role in modern lifestyle. The estimation of a meal's nutrient content is an integral component of significant diseases, such as diabetes, obesity and cardiovascular d...