AIMC Topic: Humans

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Improved Glioma Grading Using Deep Convolutional Neural Networks.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Accurate determination of glioma grade leads to improved treatment planning. The criterion standard for glioma grading is invasive tissue sampling. Recently, radiomic features have shown excellent potential in glioma-grade pre...

[Enhanced imaging in urological endoscopy].

Der Urologe. Ausg. A
White light cystoscopy and the concise documentation of pathological findings are standard diagnostic procedures in urology. Additional imaging modalities and technical innovations may support clinicians in the detection of bladder tumors. Modern end...

Transforming task representations to perform novel tasks.

Proceedings of the National Academy of Sciences of the United States of America
An important aspect of intelligence is the ability to adapt to a novel task without any direct experience (zero shot), based on its relationship to previous tasks. Humans can exhibit this cognitive flexibility. By contrast, models that achieve superh...

Optimising an FFQ Using a Machine Learning Pipeline to teach an Efficient Nutrient Intake Predictive Model.

Nutrients
Food frequency questionnaires (FFQs) are the most commonly selected tools in nutrition monitoring, as they are inexpensive, easily implemented and provide useful information regarding dietary intake. They are usually carefully drafted by experts from...

Machine learning to reveal hidden risk combinations for the trajectory of posttraumatic stress disorder symptoms.

Scientific reports
The nature of the recovery process of posttraumatic stress disorder (PTSD) symptoms is multifactorial. The Massive Parallel Limitless-Arity Multiple-testing Procedure (MP-LAMP), which was developed to detect significant combinational risk factors com...

Predicting hospitalization following psychiatric crisis care using machine learning.

BMC medical informatics and decision making
BACKGROUND: Accurate prediction models for whether patients on the verge of a psychiatric criseis need hospitalization are lacking and machine learning methods may help improve the accuracy of psychiatric hospitalization prediction models. In this pa...

Reporting of screening and diagnostic AI rarely acknowledges ethical, legal, and social implications: a mass media frame analysis.

BMC medical informatics and decision making
BACKGROUND: Healthcare is a rapidly expanding area of application for Artificial Intelligence (AI). Although there is considerable excitement about its potential, there are also substantial concerns about the negative impacts of these technologies. S...

Variable selection in social-environmental data: sparse regression and tree ensemble machine learning approaches.

BMC medical research methodology
BACKGROUND: Social-environmental data obtained from the US Census is an important resource for understanding health disparities, but rarely is the full dataset utilized for analysis. A barrier to incorporating the full data is a lack of solid recomme...