Accurate diagnosis of endoscopic mucosal healing in ulcerative colitis using deep learning and machine learning

Coronavirus disease, first detected in late 2019 (COVID-19), has spread fast throughout the world, leading to high mortality. This condition can be diagnosed using RT-PCR technique on nasopharyngeal and throat swabs with sensitivity values ranging from 30 to 70%. However, chest CT scans and X-ray images have been reported to have sensitivity values of 98 and 69%, respectively. The application of machine learning methods on CT and X-ray images has facilitated the accurate diagnosis of COVID-19. In this study, we reviewed studies which used machine and deep learning methods on chest X-ray images and CT scans for COVID-19 diagnosis and compared their performance. The accuracy of these methods ranged from 76% to more than 99%, indicating the applicability of machine and deep learning methods in the clinical diagnosis of COVID-19.

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Overview of Biological Therapy in Ulcerative Colitis: Current and Future Directions

Journal of Gastrointestinal and Liver Diseases ◽

10.15403/jgld.2014.1121.242.bezz ◽

2015 ◽

Vol 24 (2) ◽

pp. 203-213 ◽

Cited By ~ 9

Author(s):

Federica Furfaro ◽

Cristina Bezzio ◽

Sandro Ardizzone ◽

Alessandro Massari ◽

Roberto De Franchis ◽

...

Keyword(s):

Ulcerative Colitis ◽

Immunosuppressive Agents ◽

Mucosal Healing ◽

Aminosalicylic Acid ◽

Proinflammatory Mediators ◽

Experimental Drugs ◽

New Treatments ◽

Aggressive Clinical Course ◽

Near Future

The treatment of ulcerative colitis (UC) has changed over the last decade. It is extremely important to optimize the therapies which are available nowadays and commonly used in daily clinical practice, as well as to stimulate the search for more powerful drugs for the induction and maintenance of sustained and durable remission, thus preventing further complications. Therefore, it is mandatory to identify the patients' prognostic variables associated with an aggressive clinical course and to test the most potent therapies accordingly.To date, the conventional therapeutic approach based on corticosteroids, salicylates (sulfasalazine, 5-aminosalicylic acid) or immunosuppressive agents is commonly used as a first step to induce and to maintain remission. However, in recent years, knowledge of new pathogenetic mechanisms of ulcerative colitis have allowed us to find new therapeutic targets leading to the development of new treatments that directly target proinflammatory mediators, such as TNF-alpha, cytokines, membrane migration agents, cellular therapies.The aim of this review is to provide the most significant data regarding the therapeutic role of drugs in UC and to give an overview of biological and experimental drugs that will become available in the near future. In particular, we will analyse the role of these drugs in the treatment of acute flare and maintenance of UC, as well as its importance in mucosal healing and in treating patients at a high risk of relapse.

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Deep Learning Based High-Resolution Remote Sensing Image classification

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i10.384 ◽

2017 ◽

Vol 7 (10) ◽

pp. 22

Author(s):

Sumit Kaur

Keyword(s):

Machine Learning ◽

Remote Sensing ◽

Deep Learning ◽

Image Classification ◽

Language Processing ◽

Object Perception ◽

Remote Sensing Image ◽

Research Area ◽

Remote Sensing Image Classification ◽

Unsupervised Algorithms

Abstract- Deep learning is an emerging research area in machine learning and pattern recognition field which has been presented with the goal of drawing Machine Learning nearer to one of its unique objectives, Artificial Intelligence. It tries to mimic the human brain, which is capable of processing and learning from the complex input data and solving different kinds of complicated tasks well. Deep learning (DL) basically based on a set of supervised and unsupervised algorithms that attempt to model higher level abstractions in data and make it self-learning for hierarchical representation for classification. In the recent years, it has attracted much attention due to its state-of-the-art performance in diverse areas like object perception, speech recognition, computer vision, collaborative filtering and natural language processing. This paper will present a survey on different deep learning techniques for remote sensing image classification.

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Data science in economics: comprehensive review of advanced machine learning and deep learning methods

10.31232/osf.io/4pxq2 ◽

2020 ◽

Author(s):

Saeed Nosratabadi ◽

Amir Mosavi ◽

Puhong Duan ◽

Pedram Ghamisi ◽

Ferdinand Filip ◽

...

Keyword(s):

Machine Learning ◽

Deep Learning ◽

Data Science ◽

State Of The Art ◽

Science Methods ◽

Learning Models ◽

Diverse Range ◽

Hybrid Machine ◽

Economics Research

This paper provides a state-of-the-art investigation of advances in data science in emerging economic applications. The analysis was performed on novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a wide and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, was used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which, based on the accuracy metric, outperform other learning algorithms. It is further expected that the trends will converge toward the advancements of sophisticated hybrid deep learning models.

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Development and Validation of a Deep Learning Algorithm to Evaluate Endoscopic Disease Activity of Ulcerative Colitis.

Case Medical Research ◽

10.31525/ct1-nct03973437 ◽

2019 ◽

Author(s):

Keyword(s):

Ulcerative Colitis ◽

Deep Learning ◽

Disease Activity ◽

Learning Algorithm ◽

Deep Learning Algorithm ◽

Development And Validation

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Faculty Opinions recommendation of Mucosal healing predicts late outcomes after the first course of corticosteroids for newly diagnosed ulcerative colitis.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.12847957.14136055 ◽

2011 ◽

Author(s):

Mario Cottone

Keyword(s):

Ulcerative Colitis ◽

Mucosal Healing ◽

Newly Diagnosed

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Deep Learning for text in limted data settings

10.36227/techrxiv.12100692 ◽

2020 ◽

Author(s):

Pathikkumar Patel ◽

Bhargav Lad ◽

Jinan Fiaidhi

Keyword(s):

Machine Learning ◽

Time Series ◽

Deep Learning ◽

Sentiment Analysis ◽

Transfer Learning ◽

Text Classification ◽

State Of The Art ◽

Time Series Forecasting ◽

Text Data ◽

Performance Levels

During the last few years, RNN models have been extensively used and they have proven to be better for sequence and text data. RNNs have achieved state-of-the-art performance levels in several applications such as text classification, sequence to sequence modelling and time series forecasting. In this article we will review different Machine Learning and Deep Learning based approaches for text data and look at the results obtained from these methods. This work also explores the use of transfer learning in NLP and how it affects the performance of models on a specific application of sentiment analysis.

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