Explainable artificial intelligence (XAI) in biomedicine: Making AI decisions trustworthy for physicians and patients
J Lötsch, D Kringel, A Ultsch - BioMedInformatics, 2021 - mdpi.com
The use of artificial intelligence (AI) systems in biomedical and clinical settings can disrupt
the traditional doctor–patient relationship, which is based on trust and transparency in …
the traditional doctor–patient relationship, which is based on trust and transparency in …
Mining data with random forests: current options for real‐world applications
A Ziegler, IR König - Wiley Interdisciplinary Reviews: Data …, 2014 - Wiley Online Library
Random Forests are fast, flexible, and represent a robust approach to mining high‐
dimensional data. They are an extension of classification and regression trees (CART). They …
dimensional data. They are an extension of classification and regression trees (CART). They …
Consumer credit risk: Individual probability estimates using machine learning
Consumer credit scoring is often considered a classification task where clients receive either
a good or a bad credit status. Default probabilities provide more detailed information about …
a good or a bad credit status. Default probabilities provide more detailed information about …
Turning down the heat: An enhanced understanding of the relationship between urban vegetation and surface temperature at the city scale
Guiding urban planners on the cooling returns of different configurations of urban vegetation
is important to protect urban dwellers from adverse heat impacts. To this end, we estimated …
is important to protect urban dwellers from adverse heat impacts. To this end, we estimated …
[HTML][HTML] Robust probabilistic modelling of mould growth in building envelopes using random forests machine learning algorithm
Probabilistic methods can be used to account for uncertainties in hygrothermal analysis of
building envelopes. This paper presents methods for robust mould reliability analysis and …
building envelopes. This paper presents methods for robust mould reliability analysis and …
Risk estimation and risk prediction using machine-learning methods
After an association between genetic variants and a phenotype has been established,
further study goals comprise the classification of patients according to disease risk or the …
further study goals comprise the classification of patients according to disease risk or the …
Classification accuracy of transcranial magnetic stimulation for the diagnosis of neurodegenerative dementias
Objective Transcranial magnetic stimulation (TMS) has been suggested as a reliable,
noninvasive, and inexpensive tool for the diagnosis of neurodegenerative dementias. In this …
noninvasive, and inexpensive tool for the diagnosis of neurodegenerative dementias. In this …
[HTML][HTML] Classification accuracy of TMS for the diagnosis of mild cognitive impairment
Objective To evaluate the performance of a Random Forest (RF) classifier on Transcranial
Magnetic Stimulation (TMS) measures in patients with Mild Cognitive Impairment (MCI) …
Magnetic Stimulation (TMS) measures in patients with Mild Cognitive Impairment (MCI) …
[图书][B] Predicting food crises
Despite progress in reducing poverty in recent decades (World Bank Group, 2018), one in
nine people in the world faces hunger (FAO et al., 2019). More than 130 million people are …
nine people in the world faces hunger (FAO et al., 2019). More than 130 million people are …
Tree-based analysis: a practical approach to create clinical decision-making tools
M Banerjee, E Reynolds, HB Andersson… - … Quality and Outcomes, 2019 - Am Heart Assoc
Tree-based methods have become one of the most flexible, intuitive, and powerful data
analytic tools for exploring complex data structures. Tree-based methods provide a natural …
analytic tools for exploring complex data structures. Tree-based methods provide a natural …