This work introduces a predictive Length of Stay (LOS) framework for lung cancer patients using machine learning (ML) models. The framework proposed to deal with imbalanced datasets for classification-based approaches using electronic healthcare records (EHR). We have utilized supervised ML methods to predict lung cancer inpatients LOS during ICU hospitalization using the MIMIC-III dataset. Random Forest (RF) Model outperformed other models and achieved predicted results during the three framework phases. With clinical significance features selection, over-sampling methods (SMOTE and ADASYN) achieved the highest AUC results (98% with CI 95%: 95.3–100%, and 100% respectively). The combination of Over-sampling and under-sampling achieved the second-highest AUC results (98%, with CI 95%: 95.3–100%, and 97%, CI 95%: 93.7–100% SMOTE-Tomek, and SMOTE-ENN respectively). Under-sampling methods reported the least important AUC results (50%, with CI 95%: 40.2–59.8%) for both (ENN and Tomek- Links). Using ML explainable technique called SHAP, we explained the outcome of the predictive model (RF) with SMOTE class balancing technique to understand the most significant clinical features that contributed to predicting lung cancer LOS with the RF model. Our promising framework allows us to employ ML techniques in-hospital clinical information systems to predict lung cancer admissions into ICU.
This paper describes initial efforts in the form of a user research phase as part of a larger project to provide ICT based interventions to farmers in Pakistan to facilitate information dissemination. We conducted face to face interviews with 9 Pakistani farmers and 3 agricultural experts. Our main results show that mobile technology is present but under utilised, a strong peer reliance network exists and most information and media modalities are inaccessible. We relate the results obtained to design implications and future work.
Purpose
This paper narrates a case study on design thinking-based education work in an industrial design honours program. Student projects were developed in a multi-disciplinary setting across a Computing and Engineering faculty that allowed promoting technologically and user-driven innovation strategies.
Design/methodology/approach
A renewed culture and environment for industrial design (ID) students emphasised seeking functionality and fidelity, user and society value over beauty and form factors alone. The pedagogical approach sought to determine the new industrial products reality with an increasing contribution by design thinking, and its associated methodologies that are currently advancing typical ID.
Findings
In conclusion, the authors propose a number of reflections as recommendations, which may be useful for educational institutions contemplating similar curriculum makeovers to their design degrees.
Originality/value
Our research provides valuable lessons to other design courses that wish to invigorate their curriculum with technical and design thinking-based advances.
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