Prediction of Dengue-Human Protein Interaction Using Artificial Neural Network for Anti-Viral Drug Discovery

Fathima, A. Jainul; Revathy, R.; Balamurali, S.; Murugaboopathi, G.

doi:10.2139/ssrn.3356325

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“…LSTM provides neural networks with internal or short-term memory, making it particularly suitable for processing sequence-related problems such as speech classification, prediction, image subtitles, language translation, and handwriting recognition. It has been widely used to predict infectious diseases such as Dengue [ [20] , [21] , [22] ] and Malaria [ 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

LSTM algorithm optimization for COVID-19 prediction model

Sembiring,

Wahyuni,

Sediyono

2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

LSTM algorithm optimization for COVID-19 prediction model

Sembiring,

Wahyuni,

Sediyono

2024

Heliyon

View full text Add to dashboard Cite

Progress and challenges for the application of machine learning for neglected tropical diseases

2023

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Neglected tropical diseases (NTDs) continue to affect the livelihood of individuals in countries in the Southeast Asia and Western Pacific region. These diseases have been long existing and have caused devastating health problems and economic decline to people in low- and middle-income (developing) countries. An estimated 1.7 billion of the world’s population suffer one or more NTDs annually, this puts approximately one in five individuals at risk for NTDs. In addition to health and social impact, NTDs inflict significant financial burden to patients, close relatives, and are responsible for billions of dollars lost in revenue from reduced labor productivity in developing countries alone. There is an urgent need to better improve the control and eradication or elimination efforts towards NTDs. This can be achieved by utilizing machine learning tools to better the surveillance, prediction and detection program, and combat NTDs through the discovery of new therapeutics against these pathogens. This review surveys the current application of machine learning tools for NTDs and the challenges to elevate the state-of-the-art of NTDs surveillance, management, and treatment.

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Prediction of Dengue-Human Protein Interaction Using Artificial Neural Network for Anti-Viral Drug Discovery

Cited by 2 publications

References 17 publications

LSTM algorithm optimization for COVID-19 prediction model

LSTM algorithm optimization for COVID-19 prediction model

Progress and challenges for the application of machine learning for neglected tropical diseases

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