Sökning: "MIMIC-III"

Visar resultat 1 - 5 av 6 uppsatser innehållade ordet MIMIC-III.

1. 1. Towards Building Privacy-Preserving Language Models: Challenges and Insights in Adapting PrivGAN for Generation of Synthetic Clinical Text

   Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Atena Nazem; [2023]
   Nyckelord :Generative Adversarial Networks; privacy-preserving language models; clinical text data; reinforcement learning; synthetic data;

   Sammanfattning : The growing development of artificial intelligence (AI), particularly neural networks, is transforming applications of AI in healthcare, yet it raises significant privacy concerns due to potential data leakage. As neural networks memorise training data, they may inadvertently expose sensitive clinical data to privacy breaches, which can engender serious repercussions like identity theft, fraud, and harmful medical errors. LÄS MER

3. 2. An Automated Discharge Summary System Built for Multiple Clinical English Texts by Pre-trained DistilBART Model

   Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Sahel Alaei; [2023]
   Nyckelord :Language model; discharge summary; automated summary; pre- trained model; DistilBART; transformer; ROUGE; MIMIC-III;

   Sammanfattning : The discharge summary is an important document, summarizing a patient’s medical information during their hospital stay. It is crucial for communication between clinicians and primary care physicians. Creating a discharge sum- mary is a necessary task. However, it is time-consuming for physicians. LÄS MER

4. 3. Predicting Chronic Kidney Disease using a multimodal Machine Learning approach

   Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Aakruti Mishra; Navaneeth Puthiyandi; [2023]
   Nyckelord :Chronic kidney disease; Multimodal approach; ROCKET; Random Forest; XGBoost; MIMIC-III database; Data imbalance; Temporal and static modalities; Soft voting;

   Sammanfattning : Chronic Kidney Disease (CKD) is a common and dangerous health condition that requires early detection and treatment to be effective. Current diagnostic methods are time-consuming and expensive. In this research, we hope to construct a predictive model for CKD utilizing a combination of time series and static variables for early detection of CKD. LÄS MER

5. 4. Explaining Mortality Prediction With Logistic Regression

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Alva Johansson Staaf; Victor Engdahl; [2022]
   Nyckelord :Machine Learning; Logistic Regression; Mortality Prediction; Explainability; MIMIC-III;

   Sammanfattning : Explainability is a key component in building trust for computer calculated predictions when they are applied to areas with influence over individual people. This bachelor thesis project report focuses on the explanation regarding the decision making process of the machine learning method Logistic Regression when predicting mortality. LÄS MER

7. 5. Extracting Structured Data from Free-Text Clinical Notes : The impact of hierarchies in model training

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Mohammad Omer; [2021]
   Nyckelord :Diagnosis Code Assignment; Hierarchical Training; Transformer Model; BERT; SNOMED CT; ICD-9; MIMIC-III; Diagnoskodstilldelning; Hierarkisk Träning; Transformermodell; BERT; SNOMED CT; ICD-9; MIMIC-III;

   Sammanfattning : Diagnosis code assignment is a field that looks at automatically assigning diagnosis codes to free-text clinical notes. Assigning a diagnosis code to clinical notes manually needs expertise and time. Being able to do this automatically makes getting structured data from free-text clinical notes in Electronic Health Records easier. LÄS MER