This is a tentative schedule and is subject to change as deemed necessary. Additionally, to gain institutional access to weekly research papers, ensure that you are logged into through the Dartmouth VPN.
Koymemir et al., "Wearable and Implantable Sensors for Biomedical Applications" Annual Reviews on Analytical Chemistry, 2018.
Harari et al. "Using Smartphones to Collect Behavioral Data for Psychological Science: Opportunities, Practical Considerations, and Challenges" Assoc. of Psychoological Science, 2016.
Domingos, "A Few Useful Things to Know about Machine Learning," Communications of the ACM, 2012.
Vamathevan et al., "Applications of Machine Learning in Drug Discovery and Development," Nature Reviews, 2019.
Aktypi et al., "Unwinding Ariadne's Identity Thread: Privacy Risks with Fitness Trackers and Online Social Networks," Proceedings on Multimedia Privacy and Security, 2017.
Deliverables
Due Thursday, 4/2 @ 9am EST
Summary of 1 research paper. See guidelines on the assignments page.
Assignment 0 (Welcome Survey & Presentation Schedule)
Not data science but relevant - Holshue et al., "First Case of 2019 Novel Coronavirus in the United States," New England Journal of Medicine, 2020
Yan et al., "Prediction of Criticality in Patients with Severe COVID-19 infection using three clinical features: A Machine Learning-Based Prognostic Model with Clinical Data in Wuhan," medRxiv, 2020. (Presenter 4/7: Mike Zhu, pre-recorded)
Wang et al., "Abnormal Respiratory Patterns Classifier may Contribute to Large-Scale Screening of People Infected with COVID-19 in an Accurate and Unobtrusive Manner," arXiv, 2020. (Presenter 4/7: Sam Morton, live)
Halgurd et al, "A Novel AI-based Framework to Diagnose Coronavirus COVID 19 using Smartphone Embedded Sensors: Design Study," arXiv 2020. (Presenter 4/9: Roger Hallman, live)
Li et al., "Digital Health: Tracking Physiomes and Activity using Wearable Biosensors Reveals Useful Health-Related Information," PLoS Biology, 2017. (Presenter 4/9: Derek Bai, live)
Deliverables
Due on Monday, 4/6 @ 11:59PM EST
Summary of 2 research papers from this week's reading list. See guidelines on the assignment page.
Due on Tuesday, 4/7 @ 11:59PM EST
Complete Final Project Sign-Up Form. Link is posted on Canvas.
Due on Thursday, 4/9 @ 10am EST
Find and Share 1 innovative use of data for COVID-19 (details on Canvas)
Esteva et al., "Dermatologist-level classification of skin cancer with deep neural networks", Nature, 2017. (Presenter 4/14: Sydney Lister, live)
Yamashita et al., "Convolutional Neural Networks: An Overview and Application in Radiology," Insights into Imaging, 2018. (Presenter 4/14: Alejandro Martinez, live)
Kourou et al., "Machine Learning Applications in Cancer Prognosis and Prediction," Computational & Structural Biotech. Journal, 2015. (Presenter 4/16: Matthew Roth, pre-recorded)
Abreu et al., "Predicting Breast Cancer Recurrence Using Machine Learning Techniques: A Systematic Review", ACM Computing Surveys, 2016. (Presenter 4/16: Anjali Chikkula, pre-recorded)
Deliverables
Due on Monday, 4/13 @ 11:59PM EST
Summary of 2 research papers from this week's reading list. See guidelines on the assignment page.
Define Final Project Challenge/Task (must be approved by instructor)
Due on Thursday, 4/16 @ 11:59PM EST
Complete Exploratory Data Analysis & Data Description Section (first draft) for Final Paper.
Rau et al., "Development of a Web-Based Liver Cancer Prediction Model for Type II Diabetes Patience by using an Artificial Neural Network," Computer Methods and Programs in Biomedicine, 2016. (Presenter 4/21: Sahaj Shah, live)
Gulshan et al., "Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs," JAMA, 2016.
Doyle et al., "Closed-Loop Artificial Pancreas Systems: Engineering the Algorithms," Diabetes Care, 2014. (Presenter 4/23: Abigail Bartolome, live)
Wang et al., "Smartphone-Based Wound Assessment System for Patients with Diabetes," IEEE Transactions on Biomedical Engineering, 2015.
Deliverables
Due on Monday, 4/20 @ 11:59PM EST
Summary of 2 research papers from this week's reading list. See guidelines on the assignment page.
Due on Tuesday, 4/21 @ 10am EST
Your Own Idea of Using Data/Technology for COVID-19 (details on Canvas).
Due on Thursday, 4/23 @ 11:59PM EST
Complete Introduction Section & Related Work (first draft) for Final Paper.
Project Page (details on Canvas)
Takizawa et al., "Neuroimaging-aided Differential Diagnosis of the Depressive State," NeuroImage, 2014. (Presenter 4/30: Christopher Cheng, live)
Benton et al., "Multi-Task Learning for Mental Health using Social Media Text," arXiv, 2017. (Presenter 4/28: Jialing Wu, live)
Mohr et al., "Personal Sensing: Understanding Mental Health using Ubiquitous Sensors and Machine Learning," Annual Review Clin. Psychol., 2017. (Presenter 4/30: Varun Mishra, live)
Dwyer et al., "Machine Learning Approaches in Clinical Psychology and Psychiatry," Annual Review Clin. Psychol., 2018. (Presenter 4/28: Ashley Francisco, pre-recorded)
Costafreda et al., "Pattern of Neural Response to Verbal Fluency shows Diagnostic Specificity for Schizophrenia and Bipolar Disorder," BMC Psychiatry, 2011.
Deliverables
Due on Monday, 4/27 @ 11:59PM EST
Summary of 2 research papers from this week's reading list. See guidelines on the assignment page.
Milestone for Thursday, 4/30 (no submission required)
Preliminary idea of Method/Approach for Final Project challenge
Schmidt-Erfurth et al., "Artificial Intelligence in Retina," Progress in Retina and Eye Research, 2018. (Presenter 5/5: Rohan Robinson, live)
Kim et al., "Development of Machine Learning Models for Diagnosis of Glaucoma," PLOS ONE, 2017. (Presenter 5/5: Kevin Ge, live)
Fauw et al., "Clinically applicable deep learning for diagnosis and referral in retinal disease," Nature Medicine, 2018.
Srinivasan et al., "Fully Automated Detection of Diabetic Macular Edema and Dry Age-Related Macular Degeneration from Optical Coherence Tomography Images," Biomed. Optics Express, 2014.
Deliverables
Due on Monday, 5/4 @ 11:59PM EST
Summary of 2 research papers from this week's reading list. See guidelines on the assignment page.
Due on Thursday, 5/7 @ 11:59PM EST
Complete Methods Section (first draft) for Final Paper.
Hannun et al., "Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network," Nature Medicine, 2019. (Presenter 5/12: Jack Keane, live)
Martis et al. "Current Methods in Electrocardiogram Characterization," Computers in Biology and Medicine, 2014.
Orimaye et al., "Predicting Probable Alzheimer's Disease using Linguistic Deficits and Biomarkers, BMC Bioinformatics, 2017.
So et al., "Early Diagnosis of Dementia from Clinical Data by Machine Learning Techniques," Applied Sciences, 2017.
Deliverables
Due on Monday, 5/11 @ 11:59PM EST
Summary of 2 research papers from this week's reading list. See guidelines on the assignment page.
Due on Thursday, 5/14 @ 11:59PM EST
Complete Result Section (first draft) for Final Paper.
Project Time
Incorporate all feedback received for final project
Revisit and revise all sections of final paper
Project Presentations (see guidelines and schedule on the Final Project page)
Deliverables
Submit Final Presentation Slides on Canvas (due on the presentation date)
Submit Final Paper (due on Friday, 5/29 @ 11:59 PM EST).