AI Medical Compendium Topic

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Data Collection

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Adaptive kernel fuzzy clustering for missing data.

PloS one
Many machine learning procedures, including clustering analysis are often affected by missing values. This work aims to propose and evaluate a Kernel Fuzzy C-means clustering algorithm considering the kernelization of the metric with local adaptive d...

Predictive value of ATN biomarker profiles in estimating disease progression in Alzheimer's disease dementia.

Alzheimer's & dementia : the journal of the Alzheimer's Association
We aimed to evaluate the value of ATN biomarker classification system (amyloid beta [A], pathologic tau [T], and neurodegeneration [N]) for predicting conversion from mild cognitive impairment (MCI) to dementia. In a sample of people with MCI (n = 41...

Data Collection, Modeling, and Classification for Gunshot and Gunshot-like Audio Events: A Case Study.

Sensors (Basel, Switzerland)
Distinguishing between a dangerous audio event like a gun firing and other non-life-threatening events, such as a plastic bag bursting, can mean the difference between life and death and, therefore, the necessary and unnecessary deployment of public ...

A Machine Learning Framework for Balancing Training Sets of Sensor Sequential Data Streams.

Sensors (Basel, Switzerland)
The recent explosive growth in the number of smart technologies relying on data collected from sensors and processed with machine learning classifiers made the training data imbalance problem more visible than ever before. Class-imbalanced sets used ...

Machine Learning Data Augmentation as a Tool to Enhance Quantitative Composition-Activity Relationships of Complex Mixtures. A New Application to Dissect the Role of Main Chemical Components in Bioactive Essential Oils.

Molecules (Basel, Switzerland)
Scientific investigation on essential oils composition and the related biological profile are continuously growing. Nevertheless, only a few studies have been performed on the relationships between chemical composition and biological data. Herein, th...

Machine learning-based real-time object locator/evaluator for cryo-EM data collection.

Communications biology
In cryo-electron microscopy (cryo-EM) data collection, locating a target object is error-prone. Here, we present a machine learning-based approach with a real-time object locator named yoneoLocr using YOLO, a well-known object detection system. Imple...

Machine Learning-Assisted Sampling of Surfance-Enhanced Raman Scattering (SERS) Substrates Improve Data Collection Efficiency.

Applied spectroscopy
Surface-enhanced Raman scattering (SERS) is a powerful technique for sensitive label-free analysis of chemical and biological samples. While much recent work has established sophisticated automation routines using machine learning and related artific...

Graph Regularized Flow Attention Network for Video Animal Counting From Drones.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we propose a large-scale video based animal counting dataset collected by drones (AnimalDrone) for agriculture and wildlife protection. The dataset consists of two subsets, i.e., PartA captured on site by drones and PartB collected fro...

Artificial intelligence in oncology: Path to implementation.

Cancer medicine
In recent years, the field of artificial intelligence (AI) in oncology has grown exponentially. AI solutions have been developed to tackle a variety of cancer-related challenges. Medical institutions, hospital systems, and technology companies are de...