AIMC Topic: Algorithms

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A hybrid novel SVM model for predicting CO emissions using Multiobjective Seagull Optimization.

Environmental science and pollution research international
The agricultural sector is one of the most important sources of CO emissions. Thus, the current study predicted CO emissions based on data from the agricultural sectors of 25 provinces in Iran. The gross domestic product (GDP), the square of the GDP ...

The Sound of Noise in Decision-making: An Illustration with Management of Male Lower Urinary Tract Symptoms.

European urology
High-quality patient care depends on the accuracy and efficacy of clinical decision-making, which can be affected by both cognitive bias and the risk of judgment variability, which is called noise. Deep learning algorithms, artificial intelligence, a...

Towards an Optimal Footprint Based Area Coverage Strategy for a False-Ceiling Inspection Robot.

Sensors (Basel, Switzerland)
False-ceiling inspection is a critical factor in pest-control management within a built infrastructure. Conventionally, the false-ceiling inspection is done manually, which is time-consuming and unsafe. A lightweight robot is considered a good soluti...

FEA and Machine Learning Techniques for Hidden Structure Analysis.

Sensors (Basel, Switzerland)
This study focuses on investigating and predicting two hidden structures: plant root system architecture and non-visible bubbles in plexiglass. Current approaches are damaging, expensive, or time-consuming. Infrared imaging was used to study the root...

Quantum algorithm for quicker clinical prognostic analysis: an application and experimental study using CT scan images of COVID-19 patients.

BMC medical informatics and decision making
BACKGROUND: In medical diagnosis and clinical practice, diagnosing a disease early is crucial for accurate treatment, lessening the stress on the healthcare system. In medical imaging research, image processing techniques tend to be vital in analyzin...

A novel deep learning approach to extract Chinese clinical entities for lung cancer screening and staging.

BMC medical informatics and decision making
BACKGROUND: Computed tomography (CT) reports record a large volume of valuable information about patients' conditions and the interpretations of radiology images from radiologists, which can be used for clinical decision-making and further academic s...

Medical code prediction via capsule networks and ICD knowledge.

BMC medical informatics and decision making
BACKGROUND: Clinical notes record the health status, clinical manifestations and other detailed information of each patient. The International Classification of Diseases (ICD) codes are important labels for electronic health records. Automatic medica...

Study on the semi-supervised learning-based patient similarity from heterogeneous electronic medical records.

BMC medical informatics and decision making
BACKGROUND: A new learning-based patient similarity measurement was proposed to measure patients' similarity for heterogeneous electronic medical records (EMRs) data.

Co-AMPpred for in silico-aided predictions of antimicrobial peptides by integrating composition-based features.

BMC bioinformatics
BACKGROUND: Antimicrobial peptides (AMPs) are oligopeptides that act as crucial components of innate immunity, naturally occur in all multicellular organisms, and are involved in the first line of defense function. Recent studies showed that AMPs per...

A geometry-guided deep learning technique for CBCT reconstruction.

Physics in medicine and biology
Although deep learning (DL) technique has been successfully used for computed tomography (CT) reconstruction, its implementation on cone-beam CT (CBCT) reconstruction is extremely challenging due to memory limitations. In this study, a novel DL techn...