scholarly journals Designing a Machine Learning-based System to Augment the Work Processes of Medical Secretaries

2020 ◽  
Author(s):  
Patrick S. Johansen ◽  
Rune M. Jacobsen ◽  
Lukas B. L. Bysted ◽  
Mikael B. Skov ◽  
Eleftherios Papachristos
Keyword(s):  
Machine Learning ◽  
Work Processes

Optimal multispectral sensor configurations through machine learning for cognitive agriculture

2021 ◽  
Vol 69 (4) ◽  
pp. 336-344
Author(s):  
Florian Becker ◽  
Andreas Backhaus ◽  
Felix Johrden ◽  
Merle Flitter
Keyword(s):  
Machine Learning ◽  
Cost Effective ◽  
Viable Alternative ◽  
Health State ◽  
Sensor Systems ◽  
Work Processes ◽  
Non Invasive ◽  
Classification Tasks ◽  
Farming Industry ◽  
Hyperspectral Sensor

Abstract Hyperspectral sensor systems play a key role in the automation of work processes in the farming industry. Non-invasive measurements of plants allow for an assessment of the vitality and health state and can also be used to classify weeds or infected parts of a plant. However, one major downside of hyperspectral cameras is that they are not very cost-effective. In this paper, we show, that for specific tasks, multispectral systems with only a fraction of the wavelength bands and costs of a hyperspectral system can lead to promising results for regression and classification tasks. We conclude that for the ongoing automation efforts in the context of cognitive agriculture reduced multispectral systems are a viable alternative.

scholarly journals Artificial Intelligence in Healthcare

2019 ◽  
Vol 9 (5-s) ◽  
pp. 164-166 ◽  
Author(s):  
G.V.K.S. Abhinav ◽  
S Naga Subrahmanyam
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Early Stage ◽  
Clinical Decision ◽  
Current Status ◽  
Rapid Progress ◽  
Work Processes ◽  
Healthcare Data ◽  
Future Risk

Artificial intelligence is to reduce human cognitive functions. It is bringing an approach to healthcare, powdered by increasing the availability of healthcare data and rapid progress of analyst techniques. We can survey the current status of Artificial intelligence applications in healthcare and discuss its future uses. It is the most transformative technology of the 21th century. Healthcare has been identified as an early candidate to be revolutized by artificial intelligence technologies. This article aims for providing an early stage contribution with the decision making capacities of artificial intelligence technologies. The possible ethical and legally complex backdrop of the existing framework. I will conclude the present structures are largely fit to deal with the challenge of artificial intelligence are present will discuss clearly about the artificial intelligence contribution to the present health care. Artificial intelligence, machine learning, deep learning can assist with proactive patient care, reduced future risk and streamlined work processes. Keywords: Artificial intelligence, machine learning, clinical decision support.

Mind wandering as data augmentation: How mental travel supports abstraction

2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber
Keyword(s):  
Machine Learning ◽  
Data Augmentation ◽  
Mental Content ◽  
Mind Wandering ◽  
Theoretical Framework ◽  
Important Addition

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.

Machine Learning for Speaker Recognition

2020 ◽  
Author(s):  
Man-Wai Mak ◽  
Jen-Tzung Chien
Keyword(s):  
Machine Learning ◽  
Speaker Recognition

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining

Mathematics for Machine Learning

2020 ◽  
Author(s):  
Marc Peter Deisenroth ◽  
A. Aldo Faisal ◽  
Cheng Soon Ong
Keyword(s):  
Machine Learning

Phase Transitions in Machine Learning

2009 ◽  
Author(s):  
Lorenza Saitta ◽  
Attilio Giordana ◽  
Antoine Cornuejols
Keyword(s):  
Machine Learning ◽  
Phase Transitions

Understanding Machine Learning

2009 ◽  
Author(s):  
Shai Shalev-Shwartz ◽  
Shai Ben-David
Keyword(s):  
Machine Learning

Machine learning

AccessScience ◽  
2018 ◽  
Keyword(s):  
Machine Learning

Multicultural considerations in work processes

2005 ◽  
Author(s):  
Holly A. H. Handley ◽  
Nancy J. Heacox
Keyword(s):  
Work Processes
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