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Bayes Theorem

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A Survey on Blood Pressure Measurement Technologies: Addressing Potential Sources of Bias.

Sensors (Basel, Switzerland)
Regular blood pressure (BP) monitoring in clinical and ambulatory settings plays a crucial role in the prevention, diagnosis, treatment, and management of cardiovascular diseases. Recently, the widespread adoption of ambulatory BP measurement devices...

High cell density cultivation of Corynebacterium glutamicum by deep learning-assisted medium design and the subsequent feeding strategy.

Journal of bioscience and bioengineering
To improve the cell productivity of Corynebacterium glutamicum, its initial specific growth rate was improved by medium improvement using deep neural network (DNN)-assisted design with Bayesian optimization (BO) and a genetic algorithm (GA). To obtai...

Prediction and Diagnosis of Breast Cancer Using Machine and Modern Deep Learning Models.

Asian Pacific journal of cancer prevention : APJCP
UNLABELLED: Background &Objective: Carcinoma of the breast is one of the major issues causing death in women, especially in developing countries. Timely prediction, detection, diagnosis, and efficient therapies have become critical to reducing death ...

Automatic Prediction of Peak Optical Absorption Wavelengths in Molecules Using Convolutional Neural Networks.

Journal of chemical information and modeling
Molecular design depends heavily on optical properties for applications such as solar cells and polymer-based batteries. Accurate prediction of these properties is essential, and multiple predictive methods exist, from to data-driven techniques. Alt...

Convolutional neural networks combined with classification algorithms for the diagnosis of periodontitis.

Oral radiology
OBJECTIVES: We aim to develop a deep learning model based on a convolutional neural network (CNN) combined with a classification algorithm (CA) to assist dentists in quickly and accurately diagnosing the stage of periodontitis.

Application of the performance of machine learning techniques as support in the prediction of school dropout.

Scientific reports
This article presents a study, intending to design a model with 90% reliability, which helps in the prediction of school dropouts in higher and secondary education institutions, implementing machine learning techniques. The collection of information ...

Meteorological and traffic effects on air pollutants using Bayesian networks and deep learning.

Journal of environmental sciences (China)
Traffic emissions have become the major air pollution source in urban areas. Therefore, understanding the highly non-stational and complex impact of traffic factors on air quality is very important for building air quality prediction models. Using re...

Investigation on explainable machine learning models to predict chronic kidney diseases.

Scientific reports
Chronic kidney disease (CKD) is a major worldwide health problem, affecting a large proportion of the world's population and leading to higher morbidity and death rates. The early stages of CKD sometimes present without visible symptoms, causing pati...

Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data.

BMC medical informatics and decision making
Timely and accurate referral of end-stage heart failure patients for advanced therapies, including heart transplants and mechanical circulatory support, plays an important role in improving patient outcomes and saving costs. However, the decision-mak...

Artificial Intelligence-Guided Segmentation and Path Planning Software for Transthoracic Lung Biopsy.

Journal of vascular and interventional radiology : JVIR
PURPOSE: To validate the sensitivity and specificity of a 3-dimensional (3D) convolutional neural network (CNN) artificial intelligence (AI) software for lung lesion detection and to establish concordance between AI-generated needle paths and those u...