Using the TSA-LSTM two-stage model to predict cancer incidence and mortality DOI Creative Commons
Rabnawaz Khan, Jie Wang

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(2), P. e0317148 - e0317148

Published: Feb. 20, 2025

Cancer, the second-leading cause of mortality, kills 16% people worldwide. Unhealthy lifestyles, smoking, alcohol abuse, obesity, and a lack exercise have been linked to cancer incidence mortality. However, it is hard. Cancer lifestyle correlation analysis mortality prediction in next several years are used guide people's healthy lives target medical financial resources. Two key research areas this paper Data preprocessing sample expansion design Using experimental comparison, study chooses best cubic spline interpolation technology on original data from 32 entry points 420 converts annual into monthly solve problem insufficient prediction. Factor possible because sources indicate changing factors. TSA-LSTM Two-stage attention popular tool with advanced visualization functions, Tableau, simplifies paper's study. Tableau's testing findings cannot analyze predict time series data. LSTM utilized by optimization model. By commencing input feature attention, model technique guarantees that encoder converges subset sequence features during output features. As result, model's natural learning trend quality enhanced. The second step, performance maintains We can choose network improve forecasts based real-time performance. Validating source factor using Most cancers overlapping risk factors, excessive drinking, exercise, obesity breast, colorectal, colon cancer. A poor directly promotes lung, laryngeal, oral cancers, according visual tests. expected climb 18-21% between 2020 2025, 2021. Long-term projection accuracy 98.96 percent, smoking may be main causes.

Language: Английский

Using the TSA-LSTM two-stage model to predict cancer incidence and mortality DOI Creative Commons
Rabnawaz Khan, Jie Wang

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(2), P. e0317148 - e0317148

Published: Feb. 20, 2025

Cancer, the second-leading cause of mortality, kills 16% people worldwide. Unhealthy lifestyles, smoking, alcohol abuse, obesity, and a lack exercise have been linked to cancer incidence mortality. However, it is hard. Cancer lifestyle correlation analysis mortality prediction in next several years are used guide people's healthy lives target medical financial resources. Two key research areas this paper Data preprocessing sample expansion design Using experimental comparison, study chooses best cubic spline interpolation technology on original data from 32 entry points 420 converts annual into monthly solve problem insufficient prediction. Factor possible because sources indicate changing factors. TSA-LSTM Two-stage attention popular tool with advanced visualization functions, Tableau, simplifies paper's study. Tableau's testing findings cannot analyze predict time series data. LSTM utilized by optimization model. By commencing input feature attention, model technique guarantees that encoder converges subset sequence features during output features. As result, model's natural learning trend quality enhanced. The second step, performance maintains We can choose network improve forecasts based real-time performance. Validating source factor using Most cancers overlapping risk factors, excessive drinking, exercise, obesity breast, colorectal, colon cancer. A poor directly promotes lung, laryngeal, oral cancers, according visual tests. expected climb 18-21% between 2020 2025, 2021. Long-term projection accuracy 98.96 percent, smoking may be main causes.

Language: Английский

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