AIMC Topic: Artificial Intelligence

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Computer-aided classification of successional stage in subtropical Atlantic Forest: a proposal based on fuzzy artificial intelligence.

Environmental monitoring and assessment
STATEMENT OF PROBLEM: Due to the continuous variability of the forest regeneration process, patterns of indicator variables with membership in more than one successional stage may occur, making the classification of such stages a challenging and comp...

Plasma cell subtypes analyzed using artificial intelligence algorithm for predicting biochemical recurrence, immune escape potential, and immunotherapy response of prostate cancer.

Frontiers in immunology
BACKGROUND: Plasma cells as an important component of immune microenvironment plays a crucial role in immune escape and are closely related to immune therapy response. However, its role for prostate cancer is rarely understood. In this study, we inte...

OnAI-Comp: An Online AI Experts Competing Framework for Early Sepsis Detection.

IEEE/ACM transactions on computational biology and bioinformatics
Sepsis is a major public concern due to its high mortality, morbidity, and financial cost. There are many existing works of early sepsis prediction using different machine learning models to mitigate the outcomes brought by sepsis. In the practical s...

An Educational Graphical User Interface to Construct Convolutional Neural Networks for Teaching Artificial Intelligence in Radiology.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Deep learning techniques using convolutional neural networks (CNNs) have been successfully developed for various medical image analysis tasks. However, the skills to understand and develop deep learning models are not usually taught during radiology ...

Validity and reliability of a mobile digital imaging analysis trained by a four-compartment model.

Journal of human nutrition and dietetics : the official journal of the British Dietetic Association
BACKGROUND: Digital imaging analysis (DIA) estimates collected from mobile applications comprise a novel technique that can collect body composition estimates remotely without the inherent restrictions of other research-grade devices. However, the ac...

Radiation therapist perceptions on how artificial intelligence may affect their role and practice.

Journal of medical radiation sciences
INTRODUCTION: The use of artificial intelligence (AI) has increased in medical radiation science, with advanced computing and modelling. Considering radiation therapists (RTs) perceptions of how this may affect their role is imperative, as this will ...

Stature estimation by semi-automatic measurements of 3D CT images of the femur.

International journal of legal medicine
Stature estimation is one of the most basic and important methods of personal identification. The long bones of the limbs provide the most accurate stature estimation, with the femur being one of the most useful. In all the previously reported method...

Prediction and interpretation of antibiotic-resistance genes occurrence at recreational beaches using machine learning models.

Journal of environmental management
Antibiotic-resistant bacteria and antibiotic resistance genes (ARGs) are pollutants of worldwide concern that seriously threaten public health and ecosystems. Machine learning (ML) prediction models have been applied to predict ARGs in beach waters. ...

Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools.

Computers in biology and medicine
BACKGROUND: Brain cancer is a destructive and life-threatening disease that imposes immense negative effects on patients' lives. Therefore, the detection of brain tumors at an early stage improves the impact of treatments and increases the patients s...