AIMC Topic: Data Collection

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A methodology for developing dermatological datasets: lessons from retrospective data collection for AI-based applications.

BMC medical research methodology
PURPOSE: The integration of artificial intelligence into dermatological research has underscored the need for robust and well-structured dermatological datasets. However, these datasets vary widely in their development processes, and there is current...

Increasing Rigor in Online Health Surveys Through the Reduction of Fraudulent Data.

Journal of medical Internet research
Online surveys have become a key tool of modern health research, offering a fast, cost-effective, and convenient means of data collection. It enables researchers to access diverse populations, such as those underrepresented in traditional studies, an...

Developing an AI-powered wound assessment tool: a methodological approach to data collection and model optimization.

BMC medical informatics and decision making
BACKGROUND: Chronic wounds (CWs) represent a significant and growing challenge in healthcare due to their prolonged healing times, complex management, and associated costs. Inadequate wound assessment by healthcare professionals (HCPs), often due to ...

Data Collection for Automatic Depression Identification in Spanish Speakers Using Deep Learning Algorithms: Protocol for a Case-Control Study.

JMIR research protocols
BACKGROUND: Depression is a mental health condition that affects millions of people worldwide. Although common, it remains difficult to diagnose due to its heterogeneous symptomatology. Mental health questionnaires are currently the most used assessm...

Definition of reproductive structures in Eucalyptus for phenological data collection.

International journal of biometeorology
In an era where global climate change is shifting plant phenology, global meta-analyses of multiple species are required more than ever. Common language or references for enhanced data compatibility are key for such analyses. Although the Plant Pheno...

Generative AI in Medical Practice: In-Depth Exploration of Privacy and Security Challenges.

Journal of medical Internet research
As advances in artificial intelligence (AI) continue to transform and revolutionize the field of medicine, understanding the potential uses of generative AI in health care becomes increasingly important. Generative AI, including models such as genera...

Addressing bias in artificial intelligence for public health surveillance.

Journal of medical ethics
Components of artificial intelligence (AI) for analysing social big data, such as natural language processing (NLP) algorithms, have improved the timeliness and robustness of health data. NLP techniques have been implemented to analyse large volumes ...

Proceedings from the inaugural Artificial Intelligence in Primary Immune Deficiencies (AIPID) conference.

The Journal of allergy and clinical immunology
Here, we summarize the proceedings of the inaugural Artificial Intelligence in Primary Immune Deficiencies conference, during which experts and advocates gathered to advance research into the applications of artificial intelligence (AI), machine lear...

Federated clustered multi-domain learning for health monitoring.

Scientific reports
Wearable Internet of Things (WIoT) and Artificial Intelligence (AI) are rapidly emerging technologies for healthcare. These technologies enable seamless data collection and precise analysis toward fast, resource-abundant, and personalized patient car...

Relabeling for Indoor Localization Using Stationary Beacons in Nursing Care Facilities.

Sensors (Basel, Switzerland)
In this study, we propose an augmentation method for machine learning based on relabeling data in caregiving and nursing staff indoor localization with Bluetooth Low Energy (BLE) technology. Indoor localization is used to monitor staff-to-patient ass...