AIMC Topic: Smartphone

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Diagnosis of COVID-19 via acoustic analysis and artificial intelligence by monitoring breath sounds on smartphones.

Journal of biomedical informatics
Scientific evidence shows that acoustic analysis could be an indicator for diagnosing COVID-19. From analyzing recorded breath sounds on smartphones, it is discovered that patients with COVID-19 have different patterns in both the time domain and fre...

Deep learning-enabled mobile application for efficient and robust herb image recognition.

Scientific reports
With the increasing popularity of herbal medicine, high standards of the high quality control of herbs becomes a necessity, with the herb recognition as one of the great challenges. Due to the complicated processing procedure of the herbs, methods of...

Road Condition Monitoring Using Smart Sensing and Artificial Intelligence: A Review.

Sensors (Basel, Switzerland)
Road condition monitoring (RCM) has been a demanding strategic research area in maintaining a large network of transport infrastructures. With advancements in computer vision and data mining techniques along with high computing resources, several inn...

Deep learning-assisted smartphone-based molecularly imprinted electrochemiluminescence detection sensing platform: Protable device and visual monitoring furosemide.

Biosensors & bioelectronics
A novel, portable, and smartphone-based molecularly imprinted polymer electrochemiluminescence (MIP-ECL) sensing platform was constructed for sensitive and selective determination of furosemide (FSM). In this platform, MoSe nanoparticles/starch-deriv...

Artificial Intelligence Algorithms for Malware Detection in Android-Operated Mobile Devices.

Sensors (Basel, Switzerland)
With the rapid expansion of the use of smartphone devices, malicious attacks against Android mobile devices have increased. The Android system adopted a wide range of sensitive applications such as banking applications; therefore, it is becoming the ...

Examination of blood samples using deep learning and mobile microscopy.

BMC bioinformatics
BACKGROUND: Microscopic examination of human blood samples is an excellent opportunity to assess general health status and diagnose diseases. Conventional blood tests are performed in medical laboratories by specialized professionals and are time and...

Developing Affordable, Portable and Simplistic Diagnostic Sensors to Improve Access to Care.

Sensors (Basel, Switzerland)
Ophthalmology is a highly technical specialty, especially in the area of diagnostic equipment. While the field is innovative, the access to cutting-edge technology is limited with reference to the global population. A significant way to improve overa...

Agreement of anthropometric and body composition measures predicted from 2D smartphone images and body impedance scales with criterion methods.

Obesity research & clinical practice
BACKGROUND/OBJECTIVES: Body composition and anthropometry assessment from two-dimensional smartphone images is possible through advancement of computational hardware and artificial intelligence (AI) techniques. This study established agreement of a n...

An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus.

Scientific reports
Gestational Diabetes Mellitus (GDM), a common pregnancy complication associated with many maternal and neonatal consequences, is increased in mothers with overweight and obesity. Interventions initiated early in pregnancy can reduce the rate of GDM i...

Litter Detection with Deep Learning: A Comparative Study.

Sensors (Basel, Switzerland)
Pollution in the form of litter in the natural environment is one of the great challenges of our times. Automated litter detection can help assess waste occurrences in the environment. Different machine learning solutions have been explored to develo...