A5042354251- Cancer Genomics and Diagnostics
- Genetic factors in colorectal cancer
- Genomics and Phylogenetic Studies
- Colorectal Cancer Treatments and Studies
- Single-cell and spatial transcriptomics
- Colorectal Cancer Screening and Detection
- Mental Health Research Topics
- Molecular Biology Techniques and Applications
- Image and Object Detection Techniques
- EEG and Brain-Computer Interfaces
- Image Processing and 3D Reconstruction
- Handwritten Text Recognition Techniques
- CRISPR and Genetic Engineering
- Genomics and Rare Diseases
- Emotion and Mood Recognition
New York Genome Center
2022-2025
Cornell University
2022
Weill Cornell Medicine
2022
Narsee Monjee Institute of Management Studies
2018
The presence of circulating tumor DNA (ctDNA) in patients with colorectal adenomas remains uncertain. Studies using tumor‐agnostic approaches report ctDNA 10–15% patients, though uncertainty as to whether the signal originates from adenoma. To obtain an accurate estimate proportion ctDNA, a sensitive tumor‐informed strategy is preferred, it ensures detected Here, whole‐genome sequencing‐based analysis (MRD‐EDGE SNV ) was applied two independent cohorts. Cohort 1, comprising 93 stage III...
ABSTRACT In solid tumor oncology, circulating DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity ctDNA fragments in low fraction (TF) settings increase MRD sensitivity, we previously leveraged genome-wide mutational integration plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS single nucleotide variant (SNV) copy number (CNV)...
ABSTRACT Circulating cell-free DNA (ccfDNA) sequencing for low-burden cancer monitoring is limited by sparsity of circulating tumor (ctDNA), the abundance genomic material within a plasma sample, and pre-analytical error rates due to library preparation, errors. Sequencing costs have historically favored development deep targeted approaches overcoming in ctDNA detection, but these techniques are ccfDNA samples, which imposes ceiling on maximal depth coverage panels. Whole genome (WGS) an...
Artificial intelligence is a field at the intersection of computer science, mathematics, philosophy and neuroscience. Its core competency lies in shedding light on data intensive fields by generating complex relations amongst points. Depression mental condition which has bemused psychologists due to its eccentric display each individual. In this paper we peruse various sensory signals suggest ways they can be exploited effectively capture concealed patterns. Moreover also review number...
Optical Character Recognition (OCR) is an established problem statement in machine learning and artificial intelligence. While most believe it open shut case the challenge lies when data present rather ambiguous unregulated, which precisely handwritten text recognition. This paper stresses on major setbacks faced while dealing with such forms of multifarious how a finite can accommodate for this inconsistency. The specifically proposes localised zonal method character detection seen to...
Abstract In many areas of oncology, we lack sensitive tumor-burden monitoring to guide critical decision making. While circulating tumor DNA (ctDNA) promises enable disease monitoring, this approach is limited by the sparsity ctDNA in plasma. To overcome challenge, error-corrected deep targeted sequencing has been proposed. Nonetheless, framework low number genomic equivalents (GEs, ~103/mL plasma), imposing a ceiling on effective depth. We have previously shown that genome-wide mutational...