Category: Python

Please check the projects ideas from this link: https://github.com/afflint/textsent/blob/master/2023-24/projects/projects.md . I would like to implement a project based on a clinical dataset. You can choose between the “Safe Clinical NLI” (P8) project, or “Bio Linking” (P9) project. Please read also the instructions for the project which are listed in the same page, and use the same methodologies and libraries listed in the professor Cours GitHub repository. I will attach below some project examples if you need also examples of the codes you can find the GitHub of the projects below.

Introduction: Provides an overview of the project and a short dicsussion on the pertinent literature
Research question and methodology: Provides a clear statement on the goals of the project, an overview of the proposed approach, and a formal definition of the problem
Experimental results: Provides an overview of the dataset used for experiments, the metrics used for evaluating performances, and the experimental methodology. Presents experimental results as plots and/or tables
Concluding remarks: Provides a critical discussion on the experimental results and some ideas for future work. I need you to implement a study on python using google cola on this project: Bio Linking (P9)
Instructor: Darya Shlyk, Department of Computer Science, Università degli Studi di MilanoMuch of the world’s healthcare data is stored in free-text documents, such as medical records and clinical notes. Analyzing and extracting meaningful insights from this unstructured data can be challenging. One approach for extracting structured knowledge from a vast corpus of biomedical literature is to annotate the text with concepts from existing knowledge bases.In the context of biomedical information extraction, Concept Recognition (CR) is defined as a two-step process, that consists in identifying and linking textual mentions of biomedical entities, such as genes, diseases, and phenotypes, to corresponding concepts in domain-specific ontologies. The objective of this project is to devise effective strategies for automating the extraction of concepts from unstructured biomedical resources. When developing your CR system, you may decide to focus on a specific class of entities such as diseases or genes and link to any target ontology within the biomedical domain, such as MONDO, Human Phenotype Ontology, etc.For clinical CR, SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) is a viable option. SNOMED CT is a systematically organized clinical terminology that encompasses a wide range of clinical concepts, including diseases, symptoms, procedures, and body structures.DatasetPossible datasets include, PubMed abstracts and Clinical MIMIC-IV-Note available on request.ReferencesVuokko, Riikka, Anne Vakkuri, and Sari Palojoki. “Systematized Nomenclature of Medicine–Clinical Terminology (SNOMED CT) Clinical Use Cases in the Context of Electronic Health Record Systems: Systematic Literature Review.” JMIR medical informatics 11 (2023): e43750.
Lossio-Ventura, Juan Antonio, et al. “Clinical concept recognition: Evaluation of existing systems on EHRs.” Frontiers in Artificial Intelligence 5 (2023): 1051724.
Toonsi, Sumyyah, Şenay Kafkas, and Robert Hoehndorf. “BORD: A Biomedical Ontology based method for concept Recognition using Distant supervision: Application to Phenotypes and Diseases.” bioRxiv (2023): 2023-02.
Hailu, Negacy D., et al. “Biomedical concept recognition using deep neural sequence m
This is the GitHub link of the course, you can find additional informations about the models you have to use to solve this project: https://github.com/afflint/textsent/tree/master/2023-24

Hi! I need to finish a project on sentiment analysis using SpaCy and Prophet libraries. This is the final task: Overview of the pipeline you developed: forecasting, ext. regressors, fine tuning NN, news sentiment analysis, evaluation with cross validation.
Results you reached as a prediction (horizon 14 days) and as a prediction of growing/decreasing of the forex
Extra models/ideas/evaluations your group have performed. (For example evaluate the model wrt a baseline, or update the series to use all data until now, or use the scraper to get more news from the past, or use the news to directly train a classifier of growing/decreasing of the next days) This is another hint for the project: Use SpaCy Projects to classify a sentiment analysis dataset composed of reddit posts, then adapt a sentiment
analysis dataset of financial news to classify news headlines instead of reddit posts. After that, use the output of
the classifier as a Prophet regressor and evaluate the impact on prediction performance. I’ll attach below the file you need to implement the coding on, and another file we used during the lab lectures with some exercises and examples.

Hi! I need to finish a project on sentiment analysis using SpaCy and Prophet libraries. This is the final task:
Overview of the pipeline you developed: forecasting, ext. regressors, fine tuning NN, news sentiment analysis, evaluation with cross validation.
Results you reached as a prediction (horizon 14 days) and as a prediction of growing/decreasing of the forex
Extra models/ideas/evaluations your group have performed. (For example evaluate the model wrt a baseline, or update the series to use all data until now, or use the scraper to get more news from the past, or use the news to directly train a classifier of growing/decreasing of the next days) This is another hint for the project: Use SpaCy Projects to classify a sentiment analysis dataset composed of reddit posts, then adapt a sentiment analysis dataset of financial news to classify news headlines instead of reddit posts. After that, use the output of the classifier as a Prophet regressor and evaluate the impact on prediction performance. I’ll attach below the file you need to implement the coding on, and another file we used during the lab lectures with some exercises and examples.
Requirements: just complete the task of the lab | .doc file
look at the text classification file. In the first part we used SpaCy Projects to classify a sentiment analysis dataset composed of reddit posts, you need to do the same with the financial bank dataset, then use the output of the classifier as a Prophet regressor and evaluate the impact on prediction performance. Then implement a prediction (horizon 14 days) and as a prediction of growing/decreasing of the forex (merged with the other datasets). We need to use forecasting, ext. regressors, fine tuning NN, news sentiment analysis, evaluation with cross validation. Then we can also use the scraper to get more news from the past, or use the news to directly train a classifier of growing/decreasing of the next days

Assignment Requirements
Using the Python shell, execute the following functions. You will take screenshots at key points to show the successful execution. These will be placed in a single Word document. Recommended screenshot points are listed within the assigned functions, but you may add screenshots if necessary, to show the successful completion of the assignment. (Hint: Under Windows, some of these functions will accept a single backslash in a file path, while others require double backslash between folders.)
Assignment Instructions
In the Python shell, first import the sys, os, and subprocess modules.Refer to the following Python documentation for more on importing modules: Python Software Foundation. The import system.
Execute os.getlogin()Refer to Python Software Foundation. Miscellaneous operating system interfaces.
Execute os.get_exec_path()Refer to Python Software Foundation. Miscellaneous operating system interfaces. Take a screenshot.
Execute sys.pathRefer to Python Software Foundation. System-specific parameters and functions
Execute sys.byteorderRefer to Python Software Foundation. System-specific parameters and functions.
Take a screenshot.
Execute os.listdir on your C: driveRefer to Python Software Foundation. Miscellaneous operating system interfaces. Use os.mkdir to make a new folder on your C: drive named tempPythonRefer to Python Software Foundation. Miscellaneous operating system interfaces. Take a screenshot.
Use subprocess.Popen to execute the Windows dir command and have its output placed in a text file named pythonOut.txt Hint: The argument for Popen in this case will be (‘C:\windows\system32\cmd.exe “/c dir C:\ >> C:\pythonOut.txt”‘)Refer to Python Software Foundation. Subprocess management. Open pythonOut.txt in Notepad and position that window next to the Python shell window where both can be seen.
Take a screenshot.
Use subprocess.Popen to open Windows calc.exe utilityRefer to Python Software Foundation. Subprocess management.
Take a screenshot.

You have been asked to create a Pizza Ordering program that prompts the user to enter a number associated with a menu of options for their pizza order. The program should allow the user to select only one of the menu options (Small cheese pizza, Medium cheese pizza, Large cheese pizza). When the user specifies their menu option, they should be prompted to enter their topping choices (pepperoni, sausage, or olives) as follows: 1 to specify that they want the topping and 0 to specify that they do not want the topping. Each topping option costs $1.00 extra.
The goal is to calculate the order total based on the quantity specified for the menu option they chose and toppings. A confirmation of the order displays a ticket that shows what was ordered, the quantity, the menu item chosen, and the total price. Example order ticket
Thank you for your order!
Quantity: 2 Item: Small cheese pizza, no toppings – $12.00
Total: $24.00
First I need the flowchart made with Lucid chart and the Pseudocode made it with notepad. After that I need the python code.

right now we are working on how to handle the AND boolean for milestone2 part in M2.py please add the function to search method

Hello
attached is python project, I need you to do some enhancement as below:
– keep the login page as is.
– after login: there will be a window with two buttons “Report Case” and “New Case”.
– “Report Case” will open new window that includes all previous buttons except “Refresh and Report Case”. The refresh I want it automatically loop not by pressing button.
– “New Case” button will open a new window which was “Rebort Case” initially.

I am looking for someone who can do this project + I need a simple PowerPoint summarizing the project , I will share the details later. Make sure to fill out all the requirements and the code is working exactly as needed with using certain lessons we have took in our course which is introduction to programming in python ( I will share the lessons if needed) the due date is now 9 not 11 so I need it as soon as possible.

This is the project file. There are 10 pages. On page 9 there are 6 points. Only point 5 is required to be solved(interactive visualization ), and there is data that I will send to you so that you can solve point 5. I want the same codes as these slides. (i will send the pycharm file, when someone take the question).