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- ArticleOctober 2024
Deep Neural Networks for Predicting Recurrence and Survival in Patients with Esophageal Cancer After Surgery
- Yuhan Zheng,
- Jessie A. Elliott,
- John V. Reynolds,
- Sheraz R. Markar,
- Bartłomiej W. Papież,
- ENSURE study group
Cancer Prevention, Detection, and InterventionPages 176–189https://doi.org/10.1007/978-3-031-73376-5_17AbstractEsophageal cancer is a major cause of cancer-related mortality internationally, with high recurrence rates and poor survival even among patients treated with curative-intent surgery. Investigating relevant prognostic factors and predicting ...
- research-articleMay 2024
Evaluating Feature Selection Methods to Enhance Diabetes Prediction with Random Forest
- Pushpa Negi,
- AnishKumar Dhablia,
- Hrishikesh Bhanudas Vanjari,
- Jayashree Tamkhade,
- Sharayu Ikhar,
- Shrinivas T. Shirkande
ICIMMI '23: Proceedings of the 5th International Conference on Information Management & Machine IntelligenceArticle No.: 107, Pages 1–7https://doi.org/10.1145/3647444.3647934Abstract - The issue of diabetes is a significant and urgent matter in global health, necessitating the development of precise predictive models to facilitate early intervention and effective management. The objective of this study is to assess the ...
- extended-abstractJune 2023
Co-designing play activities and monitoring tools with smart interactive toys to support early intervention in Autism Spectrum Disorder and comparable neurodevelopmental conditions
IDC '23: Proceedings of the 22nd Annual ACM Interaction Design and Children ConferencePages 798–800https://doi.org/10.1145/3585088.3589927In this workshop we will present, through live demos, novel technological tools such as interactive "smart" toys for social play and AI-based monitoring tools, developed to support the early treatment of Autism Spectrum Disorder (ASD). We will discuss ...
- research-articleMay 2020
Investigation of teachers’ perspective about Early Intervention services
The Journal of Supercomputing (JSCO), Volume 76, Issue 5Pages 3440–3461https://doi.org/10.1007/s11227-018-2607-zAbstractThis survey-based, quantitative research investigated Early Intervention teachers’ perception about Early Intervention services in Mecca Region in The Kingdom of Saudi Arabia. This research focused on two dimensions of Early Intervention including ...
- research-articleSeptember 2019
Prediction of Mood Instability with Passive Sensing
- Mehrab Bin Morshed,
- Koustuv Saha,
- Richard Li,
- Sidney K. D'Mello,
- Munmun De Choudhury,
- Gregory D. Abowd,
- Thomas Plötz
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Volume 3, Issue 3Article No.: 75, Pages 1–21https://doi.org/10.1145/3351233Mental health issues, which can be difficult to diagnose, are a growing concern worldwide. For effective care and support, early detection of mood-related health concerns is of paramount importance. Typically, survey based instruments including ...