AIMC Topic: Humans

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Modeling of energy consumption factors for an industrial cement vertical roller mill by SHAP-XGBoost: a "conscious lab" approach.

Scientific reports
Cement production is one of the most energy-intensive manufacturing industries, and the milling circuit of cement plants consumes around 4% of a year's global electrical energy production. It is well understood that modeling and digitalizing industri...

Accuracy of deep learning-based integrated tooth models by merging intraoral scans and CBCT scans for 3D evaluation of root position during orthodontic treatment.

Progress in orthodontics
OBJECTIVE: This study aimed to evaluate the accuracy of deep learning-based integrated tooth models (ITMs) by merging intraoral scans and cone-beam computed tomography (CBCT) scans for three-dimensional (3D) evaluation of root position during orthodo...

Millisecond speed deep learning based proton dose calculation with Monte Carlo accuracy.

Physics in medicine and biology
Next generation online and real-time adaptive radiotherapy workflows require precise particle transport simulations in sub-second times, which is unfeasible with current analytical pencil beam algorithms (PBA) or Monte Carlo (MC) methods. We present ...

Deep learning-based brain age prediction in normal aging and dementia.

Nature aging
Brain aging is accompanied by patterns of functional and structural change. Alzheimer's disease (AD), a representative neurodegenerative disease, has been linked to accelerated brain aging. Here, we developed a deep learning-based brain age predictio...

ANNet: A Lightweight Neural Network for ECG Anomaly Detection in IoT Edge Sensors.

IEEE transactions on biomedical circuits and systems
In this paper, we propose a lightweight neural network for real-time electrocardiogram (ECG) anomaly detection and system level power reduction of wearable Internet of Things (IoT) Edge sensors. The proposed network utilizes a novel hybrid architectu...

Deep Learning-Based Computed Tomography Perfusion Imaging to Evaluate the Effectiveness and Safety of Thrombolytic Therapy for Cerebral Infarct with Unknown Time of Onset.

Contrast media & molecular imaging
This study was aimed to discuss the effectiveness and safety of deep learning-based computed tomography perfusion (CTP) imaging in the thrombolytic therapy for acute cerebral infarct with unknown time of onset. A total of 100 patients with acute cere...

Early Diagnosis of Acute Ischemic Stroke by Brain Computed Tomography Perfusion Imaging Combined with Head and Neck Computed Tomography Angiography on Deep Learning Algorithm.

Contrast media & molecular imaging
The purpose of the research was to discuss the application values of deep learning algorithm-based computed tomography perfusion (CTP) imaging combined with head and neck computed tomography angiography (CTA) in the diagnosis of ultra-early acute isc...

Classifying Characteristics of Opioid Use Disorder From Hospital Discharge Summaries Using Natural Language Processing.

Frontiers in public health
BACKGROUND: Opioid use disorder (OUD) is underdiagnosed in health system settings, limiting research on OUD using electronic health records (EHRs). Medical encounter notes can enrich structured EHR data with documented signs and symptoms of OUD and s...

Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance.

Computational intelligence and neuroscience
Student performance is crucial to the success of tertiary institutions. Especially, academic achievement is one of the metrics used in rating top-quality universities. Despite the large volume of educational data, accurately predicting student perfor...

A Study on Cross-Media Teaching Model for College English Classroom Based on Output-Driven Hypothetical Neural Network.

Computational intelligence and neuroscience
In the field of education, the development of educational big data has become an important strategic choice to promote the construction of the digital campus and educational reform, and educational big data has become a new driving force in the field...