TY  - GEN
N2  - Recent research shows that microRNAs (miRNAs) may be potential biomarkers of cancer. MiRNAs are noncoding RNA molecules that regulate gene expression in the post-transcriptional phase. When miRNA count is depleted, gene expression can become dysregulated, consequently leading to progression or drug resistance in cancer. Therefore, many researchers have begun to investigate the role of miRNA as a potential biomarker of cancer, and its role in targeted drug therapy. Artificial Intelligence has emerged as a recent breakthrough to identify cancer types with high accuracy. Even though cancer is a complex and extremely heterogeneous condition, the current practice of treating cancer -- which entails surgery, radiation therapy, chemotherapy, and immunotherapy -- is a one-size-fits-all approach that results in the prescription of the same drug for every patient with the same type and stage of cancer. This approach is expensive, time-consuming, causes the patients to suffer, and worse, prescribed cancer drugs are ineffective for 75% of the time. Machine learning can be used to deliver precision cancer therapeutics based on genomic profiles of patient's tumors.
DO  - 10.6083/xg94hq08h
DO  - DOI
AB  - Recent research shows that microRNAs (miRNAs) may be potential biomarkers of cancer. MiRNAs are noncoding RNA molecules that regulate gene expression in the post-transcriptional phase. When miRNA count is depleted, gene expression can become dysregulated, consequently leading to progression or drug resistance in cancer. Therefore, many researchers have begun to investigate the role of miRNA as a potential biomarker of cancer, and its role in targeted drug therapy. Artificial Intelligence has emerged as a recent breakthrough to identify cancer types with high accuracy. Even though cancer is a complex and extremely heterogeneous condition, the current practice of treating cancer -- which entails surgery, radiation therapy, chemotherapy, and immunotherapy -- is a one-size-fits-all approach that results in the prescription of the same drug for every patient with the same type and stage of cancer. This approach is expensive, time-consuming, causes the patients to suffer, and worse, prescribed cancer drugs are ineffective for 75% of the time. Machine learning can be used to deliver precision cancer therapeutics based on genomic profiles of patient's tumors.
AD  - Jesuit High School
T1  - A real-time miRNA-based machine learning approach for precision cancer therapeutics
DA  - 2020
AU  - Mandera, Darsh
L1  - https://digitalcollections.ohsu.edu/record/8359/files/ResearchWeek.2020.Mandera.Darsh.pdf
PB  - Oregon Health and Science University
LA  - eng
PY  - 2020
ID  - 8359
L4  - https://digitalcollections.ohsu.edu/record/8359/files/ResearchWeek.2020.Mandera.Darsh.pdf
KW  - Machine Learning
KW  - Artificial Intelligence
KW  - Biomarkers
KW  - Gene Expression
KW  - MicroRNAs
KW  - Precision Medicine
KW  - cancer
KW  - neoplasms
KW  - mirna
TI  - A real-time miRNA-based machine learning approach for precision cancer therapeutics
Y1  - 2020
L2  - https://digitalcollections.ohsu.edu/record/8359/files/ResearchWeek.2020.Mandera.Darsh.pdf
LK  - https://digitalcollections.ohsu.edu/record/8359/files/ResearchWeek.2020.Mandera.Darsh.pdf
UR  - https://digitalcollections.ohsu.edu/record/8359/files/ResearchWeek.2020.Mandera.Darsh.pdf
ER  -