Improving Children Diagnostics by Efficient Multi-label Classification Method

Glinka, Kinga; Wosiak, Agnieszka; Zakrzewska, Danuta

doi:10.1007/978-3-319-39796-2_21

Cited by 11 publications

(7 citation statements)

References 14 publications

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“…Wpływ działania impulsowego pola elektrycznego na strukturę winogron można ocenić z zastosowaniem analizy obrazów np. tomografii komputerowej [13][14][15][16][17].…”

Section: Wstępunclassified

Wpływ impulsowego pola elektrycznego na barwę wina

Gałązka-Czarnecka¹

2018

ELECTROTECHNICAL REVIEW

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Wpływ impulsowego pola elektrycznego na barwę wina Streszczenie. W artykule przedstawiono wyniki badań dotyczących wpływu impulsowego pola elektrycznego na barwę wina wyprodukowanego z winogron odmiany Hibernal. Owoce poddano działaniu impulsowego pola elektrycznego o dwóch wartości natężenia 3,3 kV/cm oraz 5 kV/cm, następnie prowadzono fermentację zgodnie z procedurami stosowanymi w przemyśle winiarskim. W uzyskanych winach oznaczono barwę metodą CIELab. Uzyskane wyniki wskazują na większą wydajność ekstrakcji związków barwnych z winogron (związków o charakterze antyoksydantów) pod wpływem PEF.

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“…Wpływ działania impulsowego pola elektrycznego na strukturę winogron można ocenić z zastosowaniem analizy obrazów np. tomografii komputerowej [13][14][15][16][17].…”

Section: Wstępunclassified

Wpływ impulsowego pola elektrycznego na barwę wina

Gałązka-Czarnecka¹

2018

ELECTROTECHNICAL REVIEW

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show abstract

“…Such systems can be used in various medical tests, such as electrocardiography (ECG), electromyography (EMG) and electroencephalography (EEG), pH level, temperature, blood pressure, breathing and many others. The multi-perspective view on patient data is necessary to improve medical decision making [40]. All these diagnostic measurements improve health care as they can be done online and the results can be wirelessly transmitted to the health center where the diagnosis on the patient's state is undertaken.…”

Section: Introductionmentioning

confidence: 99%

Applications of Smart Textiles in Post-Stroke Rehabilitation

Korzeniewska

Krawczyk

Mróz

et al. 2020

Sensors

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Stroke is a disease affecting a large part of our society. According to WHO data, it is the second world’s biggest killer, accounting for near six million deaths in 2016 and it is about 30% of the total number of strokes per year. Other patients affected by such a disease should be rehabilitated as soon as possible. As a result of this phenomenon, paresis may occur. Among the devices available on the market there are many rehabilitation robots, but the method of electrostimulation can be used. The authors focused their attention on electrostimulation and commercially available therapies. Using this method, application to people with large hand muscle contracture is difficult. The authors of the work present a solution dedicated to exactly such people. A solution of textronic sensors manufactured on a textile substrate using the technology of physical vapor deposition is presented in the article. As a result of the conducted research, an electroconductive structure was obtained with a low surface resistance value of 1 Ω/□ and high flexibility. It can alternatively be used in hand rehabilitation for electrostimulation of fingertips. The solution is dedicated to people with high hands spasticity for whom it is impossible to put on a rehabilitation glove.

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“…Unlike standard classification methods, which produce as output a class label only, multilabel classifiers (MLC) [3][4][5][6] have to provide a set of relevant labels for each processed instance. MLC has been applied to disease diagnosis in children [7], suggestion of tags for new posts in question answering forums [8], image classification [9], and identification of multi-functional enzyme [10], among other tasks. The amount of MLC algorithms proposed in the last decade is impressive.…”

Section: Introductionmentioning

confidence: 99%

“…Multilabel learning [3][4][5][6] is currently a very active field. The techniques for multilabel classification have been applied to text categorization [22], image annotation [23], tag suggestion [8] for question answering forums, and disease diagnosis in children [7], among others tasks. All these problems have a common characteristic, each one of the data patterns is linked to several labels at once, instead of only one class as in standard classification.…”

Section: Introductionmentioning

confidence: 99%

REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization

et al. 2019

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The learning from imbalanced data is a deeply studied problem in standard classification and, in recent times, also in multilabel classification. A handful of multilabel resampling methods have been proposed in late years, aiming to balance the labels distribution. However these methods have to face a new obstacle, specific for multilabel data, as is the joint appearance of minority and majority labels in the same data patterns. We proposed recently a new algorithm designed to decouple imbalanced labels concurring in the same instance, called REMEDIAL (REsampling MultilabEl datasets by Decoupling highly ImbAlanced Labels). The goal of this work is to propose a procedure to hybridize this method with some of the best resampling algorithms available in the literature, including random oversampling, heuristic undersampling and synthetic sample generation techniques. These hybrid methods are then empirically analyzed, determining how their behavior is influenced by the label decoupling process. As a result, a noteworthy set of guidelines on the combined use of these techniques can be drawn from the conducted experimentation.

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Improving Children Diagnostics by Efficient Multi-label Classification Method

Cited by 11 publications

References 14 publications

Wpływ impulsowego pola elektrycznego na barwę wina

Wpływ impulsowego pola elektrycznego na barwę wina

Applications of Smart Textiles in Post-Stroke Rehabilitation

REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization

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