Modified Needleman–Wunsch algorithm for clinical pathway clustering

Aspland, Emma; Harper, Paul Robert; Gärtner, Daniel; Webb, Philip; Barrett-Lee, Peter

doi:10.1016/j.jbi.2020.103668

Cited by 15 publications

(15 citation statements)

References 68 publications

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“…e Needleman-Wunsch algorithm proposed by Satra et al [19] was first used in biological sequence alignment algorithms. It has been widely used in many fields [20][21][22].…”

Section: Dna Comparisonmentioning

confidence: 99%

“…The Needleman–Wunsch algorithm proposed by Satra et al [ 19 ] was first used in biological sequence alignment algorithms. It has been widely used in many fields [ 20 – 22 ]. The basic idea of the dynamic programming algorithm is to score a given sequence, taking the sequence S = “ACGTACAAAT,” T = “ACGGTAG” as an example, as shown in the following formula:

…”

Section: Feedback Fast Learning Neural Network and Dna Comparison Algorithmmentioning

confidence: 99%

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[Retracted] Gene Position Index Mutation Detection Algorithm Based on Feedback Fast Learning Neural Network

Zuo

Tang

et al. 2021

Computational Intelligence and Neuroscience

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In the detection of genome variation, the research on the internal correlation of reference genome is deepening; the detection of variation in genome sequence has become the focus of research, and it has also become an effective path to find new genes and new functional proteins. The targeted sequencing sequence is used to sequence the exon region of a specific gene in cancer gene detection, and the sequencing depth is relatively large. Traditional alignment algorithms will lose some sequences, which will lead to inaccurate mutation detection. This paper proposes a mutation detection algorithm based on feedback fast learning neural network position index. By establishing a position index relationship for ACGT in the DNA sequence, the subsequence is decomposed into the position relationship of different subsequences corresponding to the main sequence. The positional relationship of the subsequence in the main sequence is determined by the positional relationship. Analyzing SNP and InDel mutations, even structural mutations, through the position correlation of sequences has the advantages of high precision and easy implementation by personal computers. The feedback fast learning neural network is used to verify whether there is a linear relationship between two or more positions. Experimental results show that the mutation points detected by position index are more than those detected by Bcftools, Freebye, Vanscan2, and Gatk.

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“…e Needleman-Wunsch algorithm proposed by Satra et al [19] was first used in biological sequence alignment algorithms. It has been widely used in many fields [20][21][22].…”

Section: Dna Comparisonmentioning

confidence: 99%

…”

Section: Feedback Fast Learning Neural Network and Dna Comparison Algorithmmentioning

confidence: 99%

[Retracted] Gene Position Index Mutation Detection Algorithm Based on Feedback Fast Learning Neural Network

Zuo

Tang

et al. 2021

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

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“…As an illustration, the common features generally necessities manual annotation, when a single word has different meanings used in different fields, and changing the meaning of words over time are the reasons for the diminishing performance of the approach. In this section, to overcome the above drawback we are using a Needleman–Wunsch algorithm [ 22 , 23 ]. To perform these modifications, Needleman–Wunsch metrics are utilized as it changes the calculation more effectively.…”

Section: Proposed Modelmentioning

confidence: 99%

Hybrid optimization and ontology-based semantic model for efficient text-based information retrieval

Kumar

Sharma

2022

J Supercomput

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Query expansion is an important approach utilized to improve the efficiency of data retrieval tasks. Numerous works are carried out by the researchers to generate fair constructive results; however, they do not provide acceptable results for all kinds of queries particularly phrase and individual queries. The utilization of identical data sources and weighting strategies for expanding such terms are the major cause of this issue which leads the model unable to capture the comprehensive relationship between the query terms. In order to tackle this issue, we developed a novel approach for query expansion technique to analyze the different data sources namely WordNet, Wikipedia, and Text REtrieval Conference. This paper presents an Improved Aquila Optimization-based COOT(IAOCOOT) algorithm for query expansion which retrieves the semantic aspects that match the query term. The semantic heterogeneity associated with document retrieval mainly impacts the relevance matching between the query and the document. The main cause of this issue is that the similarity among the words is not evaluated correctly. To overcome this problem, we are using a Modified Needleman Wunsch algorithm algorithm to deal with the problems of uncertainty, imprecision in the information retrieval process, and semantic ambiguity of indexed terms in both the local and global perspectives. The k most similar word is determined and returned from a candidate set through the top-k words selection technique and it is widely utilized in different tasks. The proposed IAOCOOT model is evaluated using different standard Information Retrieval performance metrics to compute the validity of the proposed work by comparing it with other state-of-art techniques.

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“…Uma maneira direta de representar jornadas é usando sequências de eventos [Antonelli et al 2012, Aspland et al 2021, Defossez et al 2014, Egho et al 2014, Fei and Meskens 2013, Huang et al 2012, Hur et al 2020, Le Meur et al 2015, Perer et al 2015. Nesse caso, os resultados são apresentados em forma de lista, como exemplificado na Figura 3.1.…”

Section: Representação De Jornadas De Pacientesunclassified

Modelagem, Mineração e Análise de Jornadas / Trajetórias de Pacientes

Rosa¹,

Ito²,

Vieira³

et al. 2022

Minicursos Do XXII Simpósio Brasileiro De Computação Aplicada À Saúde

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The sequence of visits and procedures performed by the patient in the health system, also known as the patient's pathway or trajectory, can reveal important information about the clinical treatment adopted and the health service provided. The rise of electronic health data availability made it possible to assess the pathways of a large number of patients. Nevertheless, some challenges also arose concerning how to synthesize these pathways and how to mine them from the data, fostering a new field of research. The objective of this mini-course is to present the area of patient pathway mining, highlighting representation models, mining techniques, methods of analysis and examples of case studies. ResumoA sequência de atendimentos e procedimentos realizados pelo paciente no sistema de saúde, a qual é denominada jornada ou trajetória do paciente, pode revelar informações importantes sobre o tratamento clínico adotado e o serviço de saúde prestado. Com o aumento no registro de dados de saúde de forma eletrônica, tornou-se possível o estudo das jornadas de um grande volume de pacientes. No entanto, surgiram também desafios sobre como sintetizar essas jornadas e de que modo extraí-las dos dados, fomentando um novo campo de pesquisa. O objetivo deste minicurso é apresentar a área de mineração de jornadas de pacientes, destacando modelos de representação, técnicas de mineração, métodos de análise e exemplos de estudos de caso. IntroduçãoO aumento de casos de doenças crônicas e de doenças agudas que deixam sequelas como a COVID-19 adicionaram outras complicações na já complexa assistência que demandam estes pacientes. Geralmente esses pacientes possuem múltiplas condições crônicas ou

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Modified Needleman–Wunsch algorithm for clinical pathway clustering

Cited by 15 publications

References 68 publications

[Retracted] Gene Position Index Mutation Detection Algorithm Based on Feedback Fast Learning Neural Network

[Retracted] Gene Position Index Mutation Detection Algorithm Based on Feedback Fast Learning Neural Network

Hybrid optimization and ontology-based semantic model for efficient text-based information retrieval

Modelagem, Mineração e Análise de Jornadas / Trajetórias de Pacientes

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