| 1. |
|
|
| 2. |
- Ylikoski, A, et al.
(författare)
-
Simultaneous quantification of prostate-specific antigen and human glandular kallikrein 2 mRNA in blood samples from patients with prostate cancer and benign disease
- 2002
-
Ingår i: Clinical Chemistry. - 0009-9147. ; 48:8, s. 1265-1271
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Detection or quantification of circulating cancer cells has been proposed as an aid in detection and monitoring of several solid tumors. We investigated the classification accuracy of prostate-specific antigen (PSA) and human glandular kallikrein 2 (hK2) mRNA copy numbers in blood for the differentiation of patients with prostate cancer (PC) and benign disease. Methods: PSA and hK2 mRNA expression was studied in blood samples from 51 men with PC and 19 men with benign disease. Among the PC patients, 10 had organ-confined disease (pT1-pT2). We used a multiplexed reverse transcription-PCR assay with two highly target-like mRNA internal standards for the simultaneous quantification of PSA and hK2 mRNA. An external calibration curve covered the range of 10(2)-10(6) mRNA copies. Results: PSA and hK2 mRNA were detected in 41 of 51 (median, 1200 copies/0.5 mL of blood) and 43 of 51 (median, 3800 copies/0.5 mL of blood) patients with PC, respectively, whereas only 1 of 19 men with benign disease was positive for both mRNAs (1500 PSA and 3100 hK2 mRNA copies/0.5 mL of blood; P < 0.0001, Mann-Whitney U-test). Of the 10 patients with organ-confined PC, only 3 with low Gleason scores (less than or equal to5) were negative for both PSA and hK2 (P = 0.02, Mann-Whitney U-test). Conclusions: The presence of PC cells in the blood circulation is an early event in PC progression, and quantitative assays for PSA and hK2 mRNA discriminate benign from PC cases. Further studies are needed to determine the diagnostic accuracy and prognostic value of the assays.
|
|
| 3. |
|
|
| 4. |
- Forsström, J. J., et al.
(författare)
-
Using data preprocessing and single layer perceptron to analyze laboratory data
- 1995
-
Ingår i: Scandinavian Journal of Clinical and Laboratory Investigation. - : Informa Healthcare. - 0036-5513 .- 1502-7686. ; 55:s222, s. 75-81
-
Tidskriftsartikel (refereegranskat)abstract
- During daily work in hospitals a large amount of clinical data is produced each day. Totally computerized patient records are not yet widely used but a large part of essential information is already stored on computer files. These include laboratory test results, diagnoses, codes for operations, codes of histopathological diagnoses and maybe even the patient's medication. Accordingly, these databases include much clinical knowledge that would be useful for clinicians.Laboratories try to support clinicians by producing reference values for laboratory tests. It is, of course, necessary information but, however, it does not give very much information about the weight of evidence that an abnormal laboratory test will give in special clinical settings.We have developed a software package - DiagaiD - in order to build a smart link between patient databases and clinicians. It utilizes neural network-based machine learning techniques and can produce decision support which meets the special needs of clinicians. From example cases it can learn clinically relevant transformations from original numeric values to logical values. By using data transformation together with a single layer perceptron it is possible to build nonlinear models from a set of preclassified example cases.In this paper, we use two small datasets to show how this scheme works in the diagnosis of acute appendicitis and in the diagnosis of myocardial infarction. Results are compared with those obtained using logistic regression or backpropagation neural networks. The performance of our neuro-fuzzy tool seemed to be slightly better in these two materials but the differences did not reach statistical significance.
|
|
| 5. |
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
|
|
| 9. |
|
|
| 10. |
|
|
