Lung cancer prediction using machine learning on data from a symptom e-questionnaire for never smokers, formers smokers and current smokers.
Elinor NemlanderAndreas Karlsson RosenbladEliya AbediSimon EkmanJan HasselströmLars E ErikssonAxel C CarlssonPublished in: PloS one (2022)
Methods or tools to assess the likelihood of lung cancer based on smoking status and to prioritize investigative and treatment measures among all patients seeking care with diffuse symptoms are much needed. Our study presents risk assessment models for patients with different smoking status that may be developed into clinical risk assessment tools that can help clinicians in assessing a patient's risk of having lung cancer.
Keyphrases
- smoking cessation
- risk assessment
- replacement therapy
- palliative care
- end stage renal disease
- healthcare
- newly diagnosed
- human health
- heavy metals
- ejection fraction
- patient reported
- mental health
- prognostic factors
- case report
- patient reported outcomes
- low grade
- machine learning
- quality improvement
- depressive symptoms
- chronic pain
- high grade
- climate change
- combination therapy
- artificial intelligence