TNJSF-2024: Projects Exhibited in Bioinformatics and Computational Biology
BF.01 :
Denoising Biomedical Images using Weakly-Supervised Deep Learning Methods
- Reeti Rout
- John P. Stevens High School
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BF.02 :
Pay Attention to the Whole (Slide) Image: Using Deep Learning to Automate Breast Cancer Histopathology
- Ritvik Gupta
- Millburn High School
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BF.03 :
medic: Multimodal Electronic Medical Records and Diagnostic Imaging-based Classifier for Detecting Pulmonary Embolisms
- Zain Jaffar
- Millburn High School
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BF.04 :
Predicting Emotion dynamics using Pretrained models and Self-supervised learning
- Ethan Wai Poon
- Edison Academy Magnet School
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BF.05 :
CoVPredict: Developing a Novel Machine Learning Platform for COVID Spike Protein Prediction for Pandemic Prevention
- Kristen Ngai
- Livingston High School
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BF.06 :
Towards Safer Consumption: Investigating the Metabolic Origins of Cucurbitacin B in Bottle Gourd (Lagenaria siceraria) Poisoning using a Stoichiometric Model
- Aria Makhija
- Morris County School of Technology
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BF.07 :
GenLSDD: A Deep Generative Approach to Ligand and Structure-based Drug Design
- Elliott Junhan Yoon
- Tenafly High School
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BF.08 :
Predicting the Effects of Bisphenol A, an Endocrine Disruptor, on Human Health Using a Physiologically-based Pharmacokinetic (PBPK) Model
- Kyuri Hailey Lim
- Bergen County Technical High School - Teterboro
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BF.09 :
Explainable Transfer Learning and Variational Autoencoder Deep Learning Network for Bee Health Assessment and Monitoring
- Eric Shen
- Ridge High School
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BF.10 :
QSAR machine learning model to predict toxic chemicals
- Derek Xie
- Livingston High School
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BF.11 :
Quantifying Exam Stress Progressions Using Electrodermal Activity and Machine Learning
- Abigail Hsu
- Newark Academy
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BF.12 :
Developing Software to Identify Osteomyelitis Staphylococcus aureus Antigens
- Nikhil Jathavedam
- Tenafly High School
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BF.13 :
Novel Deep Learning Approach and Digital Twin Technology for Wheat Yield Prediction
- Vivian J Shen
- Ridge High School
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BF.14 :
A Machine Learning Model to Identify Fabry Disease Variant and Curability by Genotype
- Ishaan Ghosh and Srivarun Kankanala
- Edison Academy Magnet School
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BF.15 :
Fine-tuning Large Language Models for Rare Disease Concept Normalization
- Andy Wang
- The Peddie School
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BF.16 :
XSpeech: A Novel Deep Learning Approach to Classifying Stutters
- Qianheng Xu
- Millburn High School
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BF.17 :
Investigations in Depression Diagnosis and Dietary Changes: An application of Machine Learning to Identify At - Risk Individuals
- Aditi Ajith Menon
- South Brunswick High School
BF.18 :
Analysis of Collective Behavior of Zebrafish using idTrackerai
- Michael Forde
- Tenafly High School