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It is preliminarily known that Aedes mosquitoes are very close to humans and their dwellings, also give rises to a broad spectrum of diseases: dengue, yellow fever, chikungunya. In this paper, we explore a multi-age-class model for mosquito…

Optimization and Control · Mathematics 2017-12-04 Karunia Putra Wijaya , Thomas Goetz , Edy Soewono

The detection of differentially expressed (DE) genes is one of the most commonly studied problems in bioinformatics. For example, the identification of DE genes between distinct disease phenotypes is an important first step in understanding…

Methodology · Statistics 2013-07-31 S. K. Ng , G. J. McLachlan , K. Wang , Z. Nagymanyoki , S. Liu , S. -W. Ng

Infectious disease forecasting is of great interest to the public health community and policymakers, since forecasts can provide insight into disease dynamics in the near future and inform interventions. Due to delays in case reporting,…

Methodology · Statistics 2022-10-12 Lauren J Beesley , Dave Osthus , Sara Y Del Valle

We have performed cough detection based on measurements from an accelerometer attached to the patient's bed. This form of monitoring is less intrusive than body-attached accelerometer sensors, and sidesteps privacy concerns encountered when…

Machine Learning · Computer Science 2022-05-12 Madhurananda Pahar , Igor Miranda , Andreas Diacon , Thomas Niesler

Accurately estimating personalized treatment effects within a study site (e.g., a hospital) has been challenging due to limited sample size. Furthermore, privacy considerations and lack of resources prevent a site from leveraging…

Machine Learning · Statistics 2022-06-17 Xiaoqing Tan , Chung-Chou H. Chang , Ling Zhou , Lu Tang

Weakly supervised methods have emerged as a powerful tool for model-agnostic anomaly detection at the Large Hadron Collider (LHC). While these methods have shown remarkable performance on specific signatures such as di-jet resonances, their…

Every year, the Aedes aegypti mosquito infects millions of people with diseases such as dengue, zika, chikungunya, and urban yellow fever. The main form to combat these diseases is to avoid mosquito reproduction by searching for and…

Computer Vision and Pattern Recognition · Computer Science 2021-11-30 Wesley L. Passos , Gabriel M. Araujo , Amaro A. de Lima , Sergio L. Netto , Eduardo A. B. da Silva

A way to enhance the performance of a model that combines genetic algorithms and fuzzy logic for feature selection and classification is proposed. Early diagnosis of any disease with less cost is preferable. Diabetes is one such disease.…

Neural and Evolutionary Computing · Computer Science 2011-03-02 E. P. Ephzibah

Intelligent systems are transforming the world, as well as our healthcare system. We propose a deep learning-based cough sound classification model that can distinguish between children with healthy versus pathological coughs such as…

Automatic objective non-invasive detection of pathological voice based on computerized analysis of acoustic signals can play an important role in early diagnosis, progression tracking and even effective treatment of pathological voices. In…

This paper describes experiments, on two domains, to investigate the effect of averaging over predictions of multiple decision trees, instead of using a single tree. Other authors have pointed out theoretical and commonsense reasons for…

Machine Learning · Computer Science 2013-04-10 Suk Wah Kwok , Chris Carter

Combining the merits of both denoising diffusion probabilistic models and gradient boosting, the diffusion boosting paradigm is introduced for tackling supervised learning problems. We develop Diffusion Boosted Trees (DBT), which can be…

Machine Learning · Statistics 2024-06-05 Xizewen Han , Mingyuan Zhou

Traditional methods of identifying pathologies in X-ray images rely heavily on skilled human interpretation and are often time-consuming. The advent of deep learning techniques has enabled the development of automated disease diagnosis…

Image and Video Processing · Electrical Eng. & Systems 2024-04-02 Dipkamal Bhusal , Sanjeeb Prasad Panday

In this paper, we apply a new promising tool for pattern classification, namely, the Tsetlin Machine (TM), to the field of disease forecasting. The TM is interpretable because it is based on manipulating expressions in propositional logic,…

Machine Learning · Computer Science 2019-06-25 K. Darshana Abeyrathna , Ole-Christoffer Granmo , Xuan Zhang , Morten Goodwin

Overconfidence in deep learning models poses a significant risk in high-stakes medical imaging tasks, particularly in multi-label classification of chest X-rays, where multiple co-occurring pathologies must be detected simultaneously. This…

Image and Video Processing · Electrical Eng. & Systems 2025-09-15 Yehudit Aperstein , Amit Tzahar , Alon Gottlib , Tal Verber , Ravit Shagan Damti , Alexander Apartsin

Dengue fever impacts populations across the tropics. Dengue is caused by a mosquito transmitted flavivirus and its burden is projected to increase under future climate and development scenarios. The transmission process of dengue virus is…

We propose an SEIR model for the populations and an SEI model for the vector to describe the transmission dynamics of a four-strain model with both primary and secondary dengue infections. In order to accomplish this, we propose and obtain…

Populations and Evolution · Quantitative Biology 2014-06-18 Raul Isea

Dengue fever is increasing in geographical range, spread by invasion of its vector mosquitoes. The trade in second-hand tires has been implicated as a factor in this process as they act as mobile reservoirs of mosquito eggs and larvae.…

Populations and Evolution · Quantitative Biology 2017-01-23 Emilene Pliego Pliego , Jorge Velázquez-Castro , Markus P. Eichhorn , Andrés Fraguela Collar

Frontotemporal dementia and Alzheimer's disease are two common forms of dementia and are easily misdiagnosed as each other due to their similar pattern of clinical symptoms. Differentiating between the two dementia types is crucial for…

Image and Video Processing · Electrical Eng. & Systems 2021-09-30 Da Ma , Donghuan Lu , Karteek Popuri , Mirza Faisal Beg

Decision trees are a commonly used class of machine learning models valued for their interpretability and versatility, capable of both classification and regression. We propose ZTree, a novel decision tree learning framework that replaces…

Machine Learning · Computer Science 2025-09-17 Eric Cheng , Jie Cheng