| bibtype |
V -
Research Report
|
| ARLID |
0538241 |
| utime |
20240103225227.4 |
| mtime |
20210121235959.9 |
| title
(primary) (eng) |
Bayesian Selective Transfer Learning for Patient-Specific Inference in Thyroid Radiotherapy |
| publisher |
| place |
Praha |
| name |
ÚTIA AV ČR |
| pub_time |
2020 |
|
| specification |
|
| edition |
| name |
Research Report |
| volume_id |
2388 |
|
| keyword |
Bayesian estimation |
| keyword |
thyroid carcinoma |
| keyword |
patient-specific inferences |
| author
(primary) |
| ARLID |
cav_un_auth*0403474 |
| name1 |
Murray |
| name2 |
Sean Ernest |
| institution |
UTIA-B |
| full_dept (cz) |
Adaptivní systémy |
| full_dept (eng) |
Department of Adaptive Systems |
| department (cz) |
AS |
| department (eng) |
AS |
| country |
IE |
| garant |
S |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0370768 |
| name1 |
Quinn |
| name2 |
Anthony |
| institution |
UTIA-B |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| full_dept |
Department of Adaptive Systems |
| country |
IE |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA18-15970S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0362986 |
|
| abstract
(eng) |
This research report outlines a selective transfer approach for Bayesian estimation of patient-specific levels of radioiodine activity in the thyroid during the treatment of differentiated thyroid carcinoma. The work seeks to address some limitations of previous approaches [4] which involve generic, non-selective transfer of archival data. It is proposed that improvements in patient-specific inferences may be achieved via transferring external population knowledge selectively. This involves matching the patient to a similar sub-population based on available metadata, generating a Gaussian Mixture Model within the partitioned data, and optimally transferring a data predictive distribution from the sub-population to the specific patient. Additionally, a performance evaluation method is proposed and early-stage results presented. |
| RIV |
BD |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10102 |
| reportyear |
2021 |
| num_of_auth |
2 |
| mrcbC52 |
4 O 4o 20231122145512.2 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0316080 |
| confidential |
S |
| arlyear |
2020 |
| mrcbTft |
\nSoubory v repozitáři: 0538241.pdf |
| mrcbU10 |
2020 |
| mrcbU10 |
Praha ÚTIA AV ČR |
|