Biomedical subjects

K Papik

Publications and source records attributed to K Papik.

4 recordsLinked to original sources

PubMed1998

[Biologic detection methods in the comparison of circulating tumor cells and micrometastases].

Early studies could not prove any diagnostic or prognostic value of the presence of tumor cells in the circulation. Recent knowledge in the field of molecular and cellular pathology provided better understanding of mechanisms of metastasis formation therefore advanced detection of circulating cancer cells has been suggested as a supplementary method of staging metastatic cancer. Beside the widely used immunocytochemical methods the reverse transcriptase-polymerase chain reaction (RT-PCR) is now the most relevant technique in studying micrometastases of solid tumors. Magnetic activated cell sorting (MACS) is a recently developed method for the enrichment of different cells from suspensions by magnetic labelling of their surface antigens. RT-PCR seems to be the most sensitive to detect circulating cancer cells or micrometastases, but it is possible by MACS to purify cells for further immunological, biochemical or genetic analysis. The aim of this review is to give a brief summary of recently used methods and to discuss the clinical relevance of the attainable results.

Biomarkers, Tumor↗

PubMed1998

[Incidence and elimination of false-negative results of ferritin determination].

Introduction of turbidimetric homogeneous immunoassays made the determination of plasma ferritin concentration wide-ranging available. However, high-dose hook effect or prozone effect occurring at samples with high ferritin concentration can lead to false-negative results. According to the authors, this phenomenon has considerable clinical significance, in patients with iron-overload disorders false-negative laboratory values may result in inaccurate diagnosis. The prozone effect can be eliminated by reaction kinetic analysis of measurements. The authors developed a neural network classification procedure based on artificial intelligence technology for the recognition of the reactions with differing kinetic flow, and made a computer software for helping the application of the classification system. False-negative results can be filtered using this new technology following the laboratory determination, thus sensitivity of plasma ferritin determination may become safe enough even in case of high concentration samples.

False Negative Reactions↗

PubMed1998

[Computerized speech recognition-based endoscopic findings].

Discrete, Hidden Markov model based speech recognition and phoneme based speech synthesis techniques were applied for gastroscopy reporting and machine control. The authors developed a special program for grammatical analysis of the sentences. Altogether 100 patient findings were grammatically analysed. The sentences were grouped according to the topographical order of the investigation: oesophagus, cardia, fundus, corpus, antrum, pylorus, bulbus, postbulbar section, and the pathological findings: erosion, ulceration, malignancy. Speech samples from 3 deep voiced male investigators were collected. The recognition rate was above 95%. A simulation program was also developed for dictation and controlling of the different equipment (monitor, printer, video, endoscope) in the gastroscopy laboratory by speech recognition. Speech synthesis was applied for the evaluation of understanding. This module artificially synthesizes the answer of the system giving backup for the understood information. With additional developments the discrete word speech 'recognition' achieved the level of routine application in medical reporting. However, ready-to-use developments need the joint activity of speech technology and endoscopy industry with end-user teams.

Diagnosis, Computer-Assisted↗

PubMed1998

[Medical use of artificial neural networks].

The main aim of the research in medical diagnostics is to develop more exact, cost-effective and handsome systems, procedures and methods for supporting the clinicians. In their paper the authors introduce a new method that recently came into the focus referred to as artificial neural networks. Based on the literature of the past 5-6 years they give a brief review--highlighting the most important ones--showing the idea behind neural networks, what they are used for in the medical field. The definition, structure and operation of neural networks are discussed. In the application part they collect examples in order to give an insight in the neural network application research. It is emphasised that in the near future basically new diagnostic equipment can be developed based on this new technology in the field of ECG, EEG and macroscopic and microscopic image analysis systems.

Artificial Intelligence↗