AIMC Topic: Machine Learning

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HARTH: A Human Activity Recognition Dataset for Machine Learning.

Sensors (Basel, Switzerland)
Existing accelerometer-based human activity recognition (HAR) benchmark datasets that were recorded during free living suffer from non-fixed sensor placement, the usage of only one sensor, and unreliable annotations. We make two contributions in this...

An IoMT-Enabled Smart Healthcare Model to Monitor Elderly People Using Machine Learning Technique.

Computational intelligence and neuroscience
The Internet of Medical Things (IoMT) enables digital devices to gather, infer, and broadcast health data via the cloud platform. The phenomenal growth of the IoMT is fueled by many factors, including the widespread and growing availability of wearab...

Making Artificial Intelligence Lemonade Out of Data Lemons: Adaptation of a Public Apical Echo Database for Creation of a Subxiphoid Visual Estimation Automatic Ejection Fraction Machine Learning Algorithm.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: A paucity of point-of-care ultrasound (POCUS) databases limits machine learning (ML). Assess feasibility of training ML algorithms to visually estimate left ventricular ejection fraction (EF) from a subxiphoid (SX) window using only apica...

Neural correlates of word representation vectors in natural language processing models: Evidence from representational similarity analysis of event-related brain potentials.

Psychophysiology
Natural language processing models based on machine learning (ML-NLP models) have been developed to solve practical problems, such as interpreting an Internet search query. These models are not intended to reflect human language comprehension mechani...

A Primer on the Present State and Future Prospects for Machine Learning and Artificial Intelligence Applications in Cardiology.

The Canadian journal of cardiology
The artificial intelligence (AI) revolution is well underway, including in the medical field, and has dramatically transformed our lives. An understanding of the basics of AI applications, their development, and challenges to their clinical implement...

Are we there yet? A machine learning architecture to predict organotropic metastases.

BMC medical genomics
BACKGROUND & AIMS: Cancer metastasis into distant organs is an evolutionarily selective process. A better understanding of the driving forces endowing proliferative plasticity of tumor seeds in distant soils is required to develop and adapt better tr...

A study of generalization and compatibility performance of 3D U-Net segmentation on multiple heterogeneous liver CT datasets.

BMC medical imaging
BACKGROUND: Most existing algorithms have been focused on the segmentation from several public Liver CT datasets scanned regularly (no pneumoperitoneum and horizontal supine position). This study primarily segmented datasets with unconventional liver...

Smart Medical Prediction for Guidance: A Mechanism Study of Machine Learning.

Journal of healthcare engineering
Data analysis and prediction have gradually attracted more and more attention in the smart healthcare industry. The smart medical prediction system is of great importance to the enterprise strategy and business development, and it is also of great va...

Intelligent Sports Video Classification Based on Deep Neural Network (DNN) Algorithm and Transfer Learning.

Computational intelligence and neuroscience
Traditional text annotation-based video retrieval is done by manually labeling videos with text, which is inefficient and highly subjective and generally cannot accurately describe the meaning of videos. Traditional content-based video retrieval uses...