AIMC Topic: Mobile Applications

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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...

Machine Learning-Based Software Defect Prediction for Mobile Applications: A Systematic Literature Review.

Sensors (Basel, Switzerland)
Software defect prediction studies aim to predict defect-prone components before the testing stage of the software development process. The main benefit of these prediction models is that more testing resources can be allocated to fault-prone modules...

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...

Automatic Fungi Recognition: Deep Learning Meets Mycology.

Sensors (Basel, Switzerland)
The article presents an AI-based fungi species recognition system for a citizen-science community. The system's real-time identification too - FungiVision - with a mobile application front-end, led to increased public interest in fungi, quadrupling t...

Soft Transducer for Patient's Vitals Telemonitoring with Deep Learning-Based Personalized Anomaly Detection.

Sensors (Basel, Switzerland)
This work addresses the design, development and implementation of a 4.0-based wearable soft transducer for patient-centered vitals telemonitoring. In particular, first, the soft transducer measures hypertension-related vitals (heart rate, oxygen satu...

Enabling Research and Clinical Use of Patient-Generated Health Data (the mindLAMP Platform): Digital Phenotyping Study.

JMIR mHealth and uHealth
BACKGROUND: There is a growing need for the integration of patient-generated health data (PGHD) into research and clinical care to enable personalized, preventive, and interactive care, but technical and organizational challenges, such as the lack of...

Advancing pharmacy and healthcare with virtual digital technologies.

Advanced drug delivery reviews
Digitalisation of the healthcare sector promises to revolutionise patient healthcare globally. From the different technologies, virtual tools including artificial intelligence, blockchain, virtual, and augmented reality, to name but a few, are provid...

Understanding the potential of emerging digital technologies for improving road safety.

Accident; analysis and prevention
Each year, 1.35 million people are killed on the world's roads and another 20-50 million are seriously injured. Morbidity or serious injury from road traffic collisions is estimated to increase to 265 million people between 2015 and 2030. Current roa...

EMPAIA App Interface: An open and vendor-neutral interface for AI applications in pathology.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Artificial intelligence (AI) apps hold great potential to make pathological diagnoses more accurate and time efficient. Widespread use of AI in pathology is hampered by interface incompatibilities between pathology software....

ACCU3RATE: A mobile health application rating scale based on user reviews.

PloS one
BACKGROUND: Over the last decade, mobile health applications (mHealth App) have evolved exponentially to assess and support our health and well-being.