AIMC Topic: Machine Learning

Clear Filters Showing 19831 to 19840 of 34417 articles

Comparison of MPL-ANN and PLS-DA models for predicting the severity of patients with acute pancreatitis: An exploratory study.

The American journal of emergency medicine
OBJECTIVE: Acute pancreatitis (AP) is a common inflammatory disorder that may develop into severe AP (SAP), resulting in life-threatening complications and even death. The purpose of this study was to explore two different machine learning models of ...

Can an inertial measurement unit (IMU) in combination with machine learning measure fast bowling speed and perceived intensity in cricket?

Journal of sports sciences
This study examined whether an inertial measurement unit (IMU), in combination with machine learning, could accurately predict two indirect measures of bowling intensity through ball release speed (BRS) and perceived intensity zone (PIZ). One IMU was...

Co-designing diagnosis: Towards a responsible integration of Machine Learning decision-support systems in medical diagnostics.

Journal of evaluation in clinical practice
RATIONALE: This paper aims to show how the focus on eradicating bias from Machine Learning decision-support systems in medical diagnosis diverts attention from the hermeneutic nature of medical decision-making and the productive role of bias. We want...

Words as a window: Using word embeddings to explore the learned representations of Convolutional Neural Networks.

Neural networks : the official journal of the International Neural Network Society
As deep neural net architectures minimize loss, they accumulate information in a hierarchy of learned representations that ultimately serve the network's final goal. Different architectures tackle this problem in slightly different ways, but all crea...

Best practices for artificial intelligence in life sciences research.

Drug discovery today
We describe 11 best practices for the successful use of artificial intelligence and machine learning in pharmaceutical and biotechnology research at the data, technology and organizational management levels.

Logistic regression and machine learning predicted patient mortality from large sets of diagnosis codes comparably.

Journal of clinical epidemiology
OBJECTIVE: The objective of the study was to compare the performance of logistic regression and boosted trees for predicting patient mortality from large sets of diagnosis codes in electronic healthcare records.

Prediction of death status on the course of treatment in SARS-COV-2 patients with deep learning and machine learning methods.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The new type of Coronavirus (2019-nCov) epidemic spread rapidly, causing more than 250 thousand deaths worldwide. The virus, which first appeared as a sign of pneumonia, was later called the SARS-COV-2 with Severe Acute Resp...

Applying machine learning, text mining, and spatial analysis techniques to develop a highway-railroad grade crossing consolidation model.

Accident; analysis and prevention
The consolidation of Highway-Railroad Grade Crossing (HRGC) is one of the effective approaches to decrease the number of crashes between trains and vehicles. From 2015-2019, there were 57 HRGC crashes at crossings in East Baton Rouge Parish (EBRP), r...

Artificial Intelligence in Nutrients Science Research: A Review.

Nutrients
Artificial intelligence (AI) as a branch of computer science, the purpose of which is to imitate thought processes, learning abilities and knowledge management, finds more and more applications in experimental and clinical medicine. In recent decades...

A Machine Learning-Based Investigation of Gender-Specific Prognosis of Lung Cancers.

Medicina (Kaunas, Lithuania)
BACKGROUND AND OBJECTIVE: Primary lung cancer is a lethal and rapidly-developing cancer type and is one of the most leading causes of cancer deaths.