Intelligence algorithm for the treatment of gastrointestinal diseases based on immune monitoring and neuroscience: A revolutionary tool for translational medicine
The research team has developed an information system based on clinical blood cell analysis and designed and implemented highly innovative algorithms. A neural network model was created based on these feature data of the blood cell population. Artificial intelligence algorithms can label susceptible...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Alexandria Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016824014686 |
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| author | Liangyu Li Xuewen Qin Guangwei Wang Siyi Li Xudong Li Lizhong Guo Javier Santos Ana María Gonzalez-Castro Yanyang Tu Yi Qin |
| author_facet | Liangyu Li Xuewen Qin Guangwei Wang Siyi Li Xudong Li Lizhong Guo Javier Santos Ana María Gonzalez-Castro Yanyang Tu Yi Qin |
| author_sort | Liangyu Li |
| collection | DOAJ |
| description | The research team has developed an information system based on clinical blood cell analysis and designed and implemented highly innovative algorithms. A neural network model was created based on these feature data of the blood cell population. Artificial intelligence algorithms can label susceptible populations for digestive tract cancer with an accuracy rate of over 80 %. A multi universe optimized BP neural network model was implemented based on TCGA data of common immune antigens in clinical laboratories. The working mechanism of this model is to assign values to the parameters of the BP neural network by using the process of searching for the best fitness in multiple universes. This model can predict the five-year survival rate of patients based on immunohistochemical data. Based on these data, an AI algorithm was used to develop a clinical prognostic model with an accuracy rate of over 99 %. The research team used single-cell sequencing data to locate cell subtypes in the features of immunohistochemical data, providing a biological basis for artificial intelligence models. The research team explored the potential biological mechanisms of cancer progression and occurrence based on gastrointestinal neuroendocrine products, and these algorithms have contributed to the prediction of cancer survival and incidence,team invented a simple and efficient algorithm. |
| format | Article |
| id | doaj-art-c6658907da764a0092f8f7095458c4ca |
| institution | Kabale University |
| issn | 1110-0168 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj-art-c6658907da764a0092f8f7095458c4ca2025-02-07T04:47:04ZengElsevierAlexandria Engineering Journal1110-01682025-02-0111391137Intelligence algorithm for the treatment of gastrointestinal diseases based on immune monitoring and neuroscience: A revolutionary tool for translational medicineLiangyu Li0Xuewen Qin1Guangwei Wang2Siyi Li3Xudong Li4Lizhong Guo5Javier Santos6Ana María Gonzalez-Castro7Yanyang Tu8Yi Qin9Office of Director of center lab, Chifeng Cancer Hospital (The Second Affiliated Hospital of Chifeng University), Cancer Research Center of Chifeng City, Second Medical Department, Chifeng University, Chifeng 024000, China; Facultad de Medicina, Universidat Autonoma de Barcelona, Bellaterra 08035, Spain; Laboratory of Neuro-Immuno-Gastroenterology, Digestive System Research Unit,Vall d Hebron Institute de Recerca (VHIR), Vall Hebron Hospital Universitari, Vall d Hebron Barcelona Hospital Campus, Barcelona 08035, Spain; Department of Information Technology, School of Computer Science, National University of Malaysia, Kuala Lumpur State, Kuala Lumpur 50000, MalaysiaOffice of Director of center lab, Chifeng Cancer Hospital (The Second Affiliated Hospital of Chifeng University), Cancer Research Center of Chifeng City, Second Medical Department, Chifeng University, Chifeng 024000, China; Corresponding author.Office of Director of center lab, Chifeng Cancer Hospital (The Second Affiliated Hospital of Chifeng University), Cancer Research Center of Chifeng City, Second Medical Department, Chifeng University, Chifeng 024000, China; Dean's Office, First Affiliated Hospital (First Clinical Medical College), Hunan Medical University, Huaihua 418000, ChinaOffice of Director of center lab, Chifeng Cancer Hospital (The Second Affiliated Hospital of Chifeng University), Cancer Research Center of Chifeng City, Second Medical Department, Chifeng University, Chifeng 024000, China; Dean's Office, First Affiliated Hospital (First Clinical Medical College), Hunan Medical University, Huaihua 418000, ChinaOffice of Director of center lab, Chifeng Cancer Hospital (The Second Affiliated Hospital of Chifeng University), Cancer Research Center of Chifeng City, Second Medical Department, Chifeng University, Chifeng 024000, China; Dean's Office, First Affiliated Hospital (First Clinical Medical College), Hunan Medical University, Huaihua 418000, ChinaNinth Clinical Medical College, Department of Medicine, Peking University, Peking 100000, ChinaLaboratory of Neuro-Immuno-Gastroenterology, Digestive System Research Unit,Vall d Hebron Institute de Recerca (VHIR), Vall Hebron Hospital Universitari, Vall d Hebron Barcelona Hospital Campus, Barcelona 08035, Spain; Department of Gastroenterology Vall d’Hebron Hospital Universitari, Vall D’Hebron Barcelona Hospital Campus, Barcelona 08035, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticasy Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, Spain; Corresponding author at: Laboratory of Neuro-Immuno-Gastroenterology, Digestive System Research Unit,Vall d Hebron Institute de Recerca (VHIR), Vall Hebron Hospital Universitari, Vall d Hebron Barcelona Hospital Campus, Barcelona 08035, Spain.Laboratory of Neuro-Immuno-Gastroenterology, Digestive System Research Unit,Vall d Hebron Institute de Recerca (VHIR), Vall Hebron Hospital Universitari, Vall d Hebron Barcelona Hospital Campus, Barcelona 08035, SpainDirector's Office, Medical Research center, Center Hospital of Huizhou City, Medical University of Guangdong, Huizhou 516000, ChinaOffice of Director of center lab, Chifeng Cancer Hospital (The Second Affiliated Hospital of Chifeng University), Cancer Research Center of Chifeng City, Second Medical Department, Chifeng University, Chifeng 024000, China; Facultad de Medicina, Universidat Autonoma de Barcelona, Bellaterra 08035, Spain; Department of Information Technology, School of Computer Science, National University of Malaysia, Kuala Lumpur State, Kuala Lumpur 50000, Malaysia; Dean's Office, First Affiliated Hospital (First Clinical Medical College), Hunan Medical University, Huaihua 418000, China; Corresponding author at: Office of Director of center lab, Chifeng Cancer Hospital (The Second Affiliated Hospital of Chifeng University), Cancer Research Center of Chifeng City, Second Medical Department, Chifeng University, Chifeng 024000, China.The research team has developed an information system based on clinical blood cell analysis and designed and implemented highly innovative algorithms. A neural network model was created based on these feature data of the blood cell population. Artificial intelligence algorithms can label susceptible populations for digestive tract cancer with an accuracy rate of over 80 %. A multi universe optimized BP neural network model was implemented based on TCGA data of common immune antigens in clinical laboratories. The working mechanism of this model is to assign values to the parameters of the BP neural network by using the process of searching for the best fitness in multiple universes. This model can predict the five-year survival rate of patients based on immunohistochemical data. Based on these data, an AI algorithm was used to develop a clinical prognostic model with an accuracy rate of over 99 %. The research team used single-cell sequencing data to locate cell subtypes in the features of immunohistochemical data, providing a biological basis for artificial intelligence models. The research team explored the potential biological mechanisms of cancer progression and occurrence based on gastrointestinal neuroendocrine products, and these algorithms have contributed to the prediction of cancer survival and incidence,team invented a simple and efficient algorithm.http://www.sciencedirect.com/science/article/pii/S1110016824014686Cancer dissectionCancer prognosisComputational biologyGastrointestinal oncologyTumor |
| spellingShingle | Liangyu Li Xuewen Qin Guangwei Wang Siyi Li Xudong Li Lizhong Guo Javier Santos Ana María Gonzalez-Castro Yanyang Tu Yi Qin Intelligence algorithm for the treatment of gastrointestinal diseases based on immune monitoring and neuroscience: A revolutionary tool for translational medicine Alexandria Engineering Journal Cancer dissection Cancer prognosis Computational biology Gastrointestinal oncology Tumor |
| title | Intelligence algorithm for the treatment of gastrointestinal diseases based on immune monitoring and neuroscience: A revolutionary tool for translational medicine |
| title_full | Intelligence algorithm for the treatment of gastrointestinal diseases based on immune monitoring and neuroscience: A revolutionary tool for translational medicine |
| title_fullStr | Intelligence algorithm for the treatment of gastrointestinal diseases based on immune monitoring and neuroscience: A revolutionary tool for translational medicine |
| title_full_unstemmed | Intelligence algorithm for the treatment of gastrointestinal diseases based on immune monitoring and neuroscience: A revolutionary tool for translational medicine |
| title_short | Intelligence algorithm for the treatment of gastrointestinal diseases based on immune monitoring and neuroscience: A revolutionary tool for translational medicine |
| title_sort | intelligence algorithm for the treatment of gastrointestinal diseases based on immune monitoring and neuroscience a revolutionary tool for translational medicine |
| topic | Cancer dissection Cancer prognosis Computational biology Gastrointestinal oncology Tumor |
| url | http://www.sciencedirect.com/science/article/pii/S1110016824014686 |
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