Results 101 to 110 of about 2,291,078 (312)
Optimizing collective fieldtaxis of swarming agents through reinforcement learning
, 2017 Swarming of animal groups enthralls scientists in fields ranging from biology to physics to engineering. Complex swarming patterns often arise from simple interactions between individuals to the benefit of the collective whole.
Elaine Norton (3667249) +3 more
core +2 more sources
Molecular Oncology, EarlyView.Urine is a rich source of biomarkers for cancer detection. Tumor‐derived material is released into the bloodstream and transported to the urine. Urine can easily be collected from individuals, allowing non‐invasive cancer detection. This review discusses the rationale behind urine‐based cancer detection and its potential for cancer diagnostics ...
Birgit M. M. Wever +1 more
wiley +1 more source
QuantuMoonLight: A low-code platform to experiment with quantum machine learning
SoftwareX, 2023 Nowadays, machine learning is being used to address multiple problems in various research fields, with software engineering researchers being among the most active users of machine learning mechanisms.
Francesco Amato +18 more
doaj
Personalized Physical Activity Coaching: A Machine Learning Approach [PDF]
Sensors, 2018 Living a sedentary lifestyle is one of the major causes of numerous health problems. To encourage employees to lead a less sedentary life, the Hanze University started a health promotion program. One of the interventions in the program was the use of an activity tracker to record participants' daily step count.
Talko B. Dijkhuis +4 more
openaire +4 more sources
Molecular Oncology, EarlyView.Circulating tumor DNA (ctDNA) offers a possibility for different applications in early and late stage breast cancer management. In early breast cancer tumor informed approaches are increasingly used for detecting molecular residual disease (MRD) and early recurrence. In advanced stage, ctDNA provides a possibility for monitoring disease progression and
Eva Valentina Klocker +14 more
wiley +1 more source
APL Machine Learning, 2023 The discovery of the molecular candidates for application in drug targets, biomolecular systems, catalysts, photovoltaics, organic electronics, and batteries necessitates the development of machine learning algorithms capable of rapid exploration of ...
Ayana Ghosh +2 more
doaj +1 more source
Privacy-preserving machine learning based on secure two-party computations
Безопасность информационных технологий, 2021 The paper is devoted to the analysis of privacy-preserving machine learning systems based on secure two-party computations. The paper provides introductory information about privacy-preserving machine learning systems, analyses the goals and objectives ...
Sergey V. Zapechnikov +1 more
doaj +1 more source
An Active Instance-based Machine Learning method for Stellar Population Studies
, 2005 We have developed a method for fast and accurate stellar population parameters determination in order to apply it to high resolution galaxy spectra. The method is based on an optimization technique that combines active learning with an instance-based ...
Fuentes, Olac +3 more
core +1 more source
Unlabeled data selection for active learning in image classification
Scientific ReportsActive Learning has emerged as a viable solution for addressing the challenge of labeling extensive amounts of data in data-intensive applications such as computer vision and neural machine translation.
Xiongquan Li +5 more
semanticscholar +1 more source
Cell‐free and extracellular vesicle microRNAs with clinical utility for solid tumors
Molecular Oncology, EarlyView.Cell‐free microRNAs (cfmiRs) are small‐RNA circulating molecules detectable in almost all body biofluids. Innovative technologies have improved the application of cfmiRs to oncology, with a focus on clinical needs for different solid tumors, but with emphasis on diagnosis, prognosis, cancer recurrence, as well as treatment monitoring.
Yoshinori Hayashi +6 more
wiley +1 more source