User:KonradJ

2023 Week 1: (May 30th - June 4th)

Tuesday (5/30)

• Attended REU oreintation
• Met with peers and mentors

Wednesday (5/31)

• Attended lecture lead by Brylow about research papers and how to log progress properly
• Met with mentor to talk about goals and milestones and shared research papers to read (will update tomorrow)

Thursday (6/1)

• Sadly most of my day was consumed with moving into my apartment so minimized my ability to work
• Went over my first research paper with a surface level reading.
  • Assessment of Medical Reports Uncertainity through Topic Modeling and Machine Learning

Friday (6/2)

• Read various research articles including the one from yesterday more thoroughly
  • Effects of Negation and Uncertainty Stratification on Text-Derived Patient Profile SImilarity
  • Extracting Medical Information From Free-Text and Unstructured Patient-Generated Health Data Using Natural Language Processing Methods: Feasibility Study With Real-world Data
• Took notes on what I wrote later

Sunday (6/4)

• Took more notes on the research papers I've already read
• Began a lengthy research paper
  • Negation and uncertainty detection in clinical texts written in Spanish: a deep learning-based approach
• Prepared Log for this upcoming week

2023 Week 2: (June 5th - June 11th)

Monday (6/5)

• Met with group for federally mandated training.

Tuesday (6/6)

• Met with peers and discussed where evyerone was at in their process
• Finished the lengthy research paper from the other day
• Read the last of my research papers
  • Challenges and opportunities beyond structured data in analysis of electronic health records
• Got up to the first lab of a coursera course recommended by my mentor

Wednesday (6/7)

• Completed 2 coursera labs
• Met with peers and discussed milestones before hearing a lecture on technical writing and presenting from Dr. Brylow
• Met with my mentor and talked about goals for this week
  • Reviewing the relevent data in the form of csv files

Thursday (6/8)

• Got to the end of the first section of coursera and began the lab associated
• Began looking at relevent files for the summer project
  • Csv files that contain patient data that we will use to practice uncertainty quantifying strategies

Friday (6/9)

• Dug deeper into research papers I had read to find what the most perteinent files were for the MIMIC-III dataset
  • Seems like the best dataset for us would be the D_ICD_DIAGNOSES.csv which has ICD-9 codes for each diagnoses
• Continued online natural language processing course through coursera
  • Naive Bayes, Bayes Rule, Laplacian smoothing, and log likelihood

Sunday (6/11)

• Completed week 2 on Naive Bayes in Coursera
  • Got passing grade on week 2 quiz on material and completed all labs
• Started Week 3 course on Vector Space Models
  • Completed a couple labs
• Prepared log for upcoming week

2023 Week 3: (June 12th - June 16th)

Monday (6/12)

• Completed Week 3 courses for the Coursera class I am taking
  • Vector Space Models
• Dug more into the ICD_9 records

Tuesday (6/13)

• Completed labs from week 1 and week 2 of coursera course
  • Logistic Regression and Naive Bayes

Wednesday (6/14)

• Heard research talk from Dr. Praveen
• Talked with peers about where they are in their projects
• Continued with week 4 of coursera lectures

Thursday (6/15)

• Finished week 4 of coursera lectures
  • Machine Translation and Document Search
• Did week 3 lab for coursera
  • Vector Space Models

Friday (6/16)

• Began messing with preprocessing functions with some columns of the dataset (MIMIC-III, D_ICD_DIAGNOSES)
  • Removed punctuation, made lowercase, tokenized, then stemmed the columns
• Continued to read up on relevent information about how to preprocess and word2vector strategies

2023 Week 3: (June 19th - June 23rd )

Tuesday (6/20)

• Re-read one of the more valuable research papers to get an idea of where to go from here after learning more about the relevent technologies and algorithms
• Reviewed coursera materials to better understand the steps in the process of natural language processing
• Continued to tinker with the data with preprocessing before I get more in depth this week

Wednesday (6/21)

• Listened to a great research lecture from Dr. Walt Bialkowski on using data science to predict food shortages at local pantries
• Talked with peers about their projects after the lecture
• Began creating some slides and reviewing materials for mini-presentation

Thursday (6/22)

• Met with my mentor to talk about mini-presentation coming up next week as well as adjustments to my pre-processing methods and what to do next
• Continued with creation of the mini-presentation and script to go along with it

Friday (6/23)

2023 Week 4: (June 26th - June 30th)

Monday (6/26)

• Reviewed papers and other materials for writing script out for presentation
• Created some slides

Tuesday (6/27)

• Wrote the script for talk
• Finished presentation slides
• Practiced until I felt comfortable with the material

Wednesday (6/28)

• Gave presentation to my peers
• Talked with them after about their projects and upcoming plans

Thursday (6/29)

• Met with my mentor to establish game plan for this week and the upcoming weeks
• Watched some videos on approaches to the BERT model and picked out some artciles

Friday (6/30)

• Read thorough artciles with implmentation notes and code
• Started to attempt implementing myself
• Found a new implementation I liked, confused on how to split up the data or if I should be even doing that before I apply the model
• Talked with mentor about slowing down and just working on BOW model, too big picture right now

2023 Week 5:( July 3rd - July 7th )

Monday (7/3)

• Reviewed two research papers for content and ideas on methodology
• Worked to complete BOW models after slowing down and attempting to take it step by step
  • Had some problems with tokenization and stemming attempting to iron those out
• Word count has also been a problem and trying to find out if its in the preprocessing or model itself

Tuesday (7/4)

Wednesday (7/5)

• Watched the rest of my peers' research presentations
• Looked at some other tokenization methods to help with current preprocessing bug
• Reviewd Coursera notes and videos they have to refresh on concepts

Thursday (7/6)

• Reviewed more of the coursera materials
• Conintued to look into different tokenizers

Friday (7/7)

• Ran into some trouble with stemming so looked into different methods.
• Still have't been able to deal with a tokenization error that effects BOW
• Continued review of Coursera materials

2023 Week 6:( July 10th - July 14th )

Monday (7/10)

• Tinkered with preprocessed text attempting to get it into vector form
• Looked into alternatives to CountVectorizer()
• Made a new notebook and tried different ways of preprocessing data when CountVectorizer() is involved

Tuesday (7/11)

Wednesday (7/12)

Thursday (7/13)

Friday (7/14)