AIMC Topic: Machine Learning

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Augmented Analytics Driven by AI: A Digital Transformation beyond Business Intelligence.

Sensors (Basel, Switzerland)
Lately, Augmented Analytics (AA) has increasingly been introduced as a tool for transforming data into valuable insights for decision-making, and it has gained attention as one of the most advanced methods to facilitate modern analytics for different...

A Survey on Medical Explainable AI (XAI): Recent Progress, Explainability Approach, Human Interaction and Scoring System.

Sensors (Basel, Switzerland)
The emerging field of eXplainable AI (XAI) in the medical domain is considered to be of utmost importance. Meanwhile, incorporating explanations in the medical domain with respect to legal and ethical AI is necessary to understand detailed decisions,...

Matched Filter Interpretation of CNN Classifiers with Application to HAR.

Sensors (Basel, Switzerland)
Time series classification is an active research topic due to its wide range of applications and the proliferation of sensory data. Convolutional neural networks (CNNs) are ubiquitous in modern machine learning (ML) models. In this work, we present a...

Development and Evaluation of Machine Learning-Based High-Cost Prediction Model Using Health Check-Up Data by the National Health Insurance Service of Korea.

International journal of environmental research and public health
In this study, socioeconomic, medical treatment, and health check-up data from 2010 to 2017 of the National Health Insurance Service (NHIS) of Korea were analyzed. This year's socioeconomic, treatment, and health check-up data are used to develop a p...

Advancing molecular graphs with descriptors for the prediction of chemical reaction yields.

Journal of computational chemistry
Chemical yield is the percentage of the reactants converted to the desired products. Chemists use predictive algorithms to select high-yielding reactions and score synthesis routes, saving time and reagents. This study suggests a novel graph neural n...

Applying interpretable machine learning workflow to evaluate exposure-response relationships for large-molecule oncology drugs.

CPT: pharmacometrics & systems pharmacology
The application of logistic regression (LR) and Cox Proportional Hazard (CoxPH) models are well-established for evaluating exposure-response (E-R) relationship in large molecule oncology drugs. However, applying machine learning (ML) models on evalua...

A Systematic Review of Time Series Classification Techniques Used in Biomedical Applications.

Sensors (Basel, Switzerland)
Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, and ingestible and implantable sensors are increasingly used by individuals and clinicians to capture the health outcomes or b...

Detecting Reconnaissance and Discovery Tactics from the MITRE ATT&CK Framework in Zeek Conn Logs Using Spark's Machine Learning in the Big Data Framework.

Sensors (Basel, Switzerland)
While computer networks and the massive amount of communication taking place on these networks grow, the amount of damage that can be done by network intrusions grows in tandem. The need is for an effective and scalable intrusion detection system (ID...

Explainable machine learning methods and respiratory oscillometry for the diagnosis of respiratory abnormalities in sarcoidosis.

BMC medical informatics and decision making
BACKGROUND: In this work, we developed many machine learning classifiers to assist in diagnosing respiratory changes associated with sarcoidosis, based on results from the Forced Oscillation Technique (FOT), a non-invasive method used to assess pulmo...

Hyperspectral imaging for chemicals identification: a human-inspired machine learning approach.

Scientific reports
Data analysis has increasingly relied on machine learning in recent years. Since machines implement mathematical algorithms without knowing the physical nature of the problem, they may be accurate but lack the flexibility to move across different dom...