Sökning: "label machine"

Visar resultat 1 - 5 av 121 uppsatser innehållade orden label machine.

1. 1. Utilizing Transformers with Domain-Specific Pretraining and Active Learning to Enable Mining of Product Labels

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för beräkningsvetenskap

   Författare :Erik Norén; [2023]
   Nyckelord :Machine Learning; Natural Language Processing; NLP; BERT; Active Learning; AL; Pharmacovigilance; UMC; Uppsala Monitoring Centre; Structured Product Label; SPL; Transformers; Domain-Specific Pretraining; NER; Named Entity Recognition; Adverse Drug Reaction; ADR;

   Sammanfattning : Structured Product Labels (SPLs), the package inserts that accompany drugs governed by the Food and Drugs Administration (FDA), hold information about Adverse Drug Reactions (ADRs) that exists associated with drugs post-market. This information is valuable for actors working in the field of pharmacovigilance aiming to improve the safety of drugs. LÄS MER

3. 2. Machine Learning Clustering andClassification of Network DeploymentScenarios in a Telecom Networksetting

   Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

   Författare :Chayan Shrang Raj; [2023]
   Nyckelord :Telecommunications; Statistics; Machine Learning; Masters; PySpark; Python; Data Visualization; LTE; eNodeB; Data analysis; Data Science; AI; Jupyter; HDFS;

   Sammanfattning : Cellular network deployment scenarios refer to how cellular networks are implementedand deployed by network operators to provide wireless connectivity to end users.These scenarios can vary based on capacity requirements, type of geographical area, populationdensity, and specific use cases. LÄS MER

4. 3. Evaluating the Effect of Meta-Labeling on Equity Market Neutral Strategy

   Kandidat-uppsats, Lunds universitet/Statistiska institutionen

   Författare :Niclas Wölner-Hanssen; [2023]
   Nyckelord :Meta-Labeling; Probabilistic Sharpe Ratio; Equity Market Neutral; Mathematics and Statistics;

   Sammanfattning : This thesis aims to construct an Equity Market Neutral (EMN) strategy framework to predict intraday excess returns of stocks within the S&P 500 index by utilizing machine learning techniques proposed by (López de Prado, 2018). The constructed EMN strategies within the framework utilizes techniques such as Stacked Single Feature Importance (SSFI), sample weighting, Probabilistic Sharpe Ratio (PSR), and meta-labeling. LÄS MER

5. 4. Quantification of DNA Nanoballs Using Image Processing Techniques

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen Vi3

   Författare :Sara Lindberg; [2023]
   Nyckelord :image analysis; fluorescence microscopy; quantification; DNA; rolling circle amplification; machine learning; deep learning; transfer learning; neural networks;

   Sammanfattning : In gene editing, it is important to identify the number of edited and unedited nucleic acids in the development of new therapies and drugs. Countagen is developing a technology for accelerating genomic research and their product is called GeneAbacus. LÄS MER

7. 5. Optic nerve sheath diameter semantic segmentation and feature extraction

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

   Författare :Simone Bonato; [2023]
   Nyckelord :Machine Learning; Computer Vision; Image Segmentation; Medical Imaging; Optic Nerve Sheath Diameter; nnU-Net; Maskininlärning; datorseende; bildsegmentering; medicinsk bildbehandling; optisk nervslidsdiameter; nnU-Net;

   Sammanfattning : Traumatic brain injury (TBI) affects millions of people worldwide, leading to significant mortality and disability rates. Elevated intracranial pressure (ICP) resulting from TBI can cause severe complications and requires early detection to improve patient outcomes. LÄS MER