Wotsɔa dodokpɔ kple dɔdamɔnu vovovowo léa ŋku ɖe dzitodzito me kansa ŋu, eye dɔdamɔnu siawo dometɔ aɖewoe nye:
1. Dɔléle si me nènɔ tsã kple dodokpɔ si nàwɔ na wò: Ðɔkta la abia nya wò tso wò dɔlélea ƒe dzesiwo, sigaretnono, kple dzitodzito me kansa si le wò ƒometɔwo ŋu la ŋu.
Woado wò kpɔ hã be woanya dɔlélea ƒe dzesiwo.
2. Fotowo kpɔkpɔ: Zi geɖe la, wozãa akɔta ƒe foto si nye X-ray kple kɔmpiuta ƒe foto si nye tomography (CT) tsɔ kpɔa dzitodzito kple akpa siwo ƒo xlãe ƒe fotowo tsitotsito.
Dodokpɔ siawo ate ŋu akpe ɖe ame ŋu wòakpɔ nu siwo mele abe lãmekawo ene o, abe nutetewo alo nu siwo ate ŋu afia be dzitodzito me kansa le amea ŋu.
3. Aɖitsi ƒe dɔwɔwɔ: Wotsɔa nusuekpɔmɔ̃ léa ŋku ɖe wò aɖitsi (aɖitsi si nènyã tso dzitodzito me) ƒe ɖe ŋu be woakpɔ kansa me nugbagbeviwo hã.
4. Dɔdzẽŋusẽ ɖeɖefia: Woɖea dzitodzito me lãmeka aɖe eye wodzroa eme le nusuekpɔmɔ̃ dzi be woakpɔe ɖa be kansa me nugbagbeviwo le eme hã.
Woate ŋu awɔ esia to aŋutrɔ me dodokpɔ, abui me dodokpɔ, alo dɔdada me dodokpɔ me.
5. Aɖitikewo me toto: Wotsɔa nu sue aɖe si me akaɖi le si me fotoɖemɔ̃ le dea ŋɔti alo nu me eye wòyina ɖe veme be woado dzitodzitowo kple dzitodzitowo kpɔ.
Woate ŋu azã mɔnu sia atsɔ aɖe lãmekawo le lãme na ame.
6. Aɖinu sue aɖe tsɔtsɔ do dzitodzito me (FNA): Wotsɔa abui sue aɖe dea dzitodzito me nu si me lãmenugbagbevi aɖewo le me be woadoe akpɔ.
7. Akɔdzidodokpɔ: Wozãa abui tsɔ ɖea tsi le teƒe si le dzitodzito kple akɔta dome, eye wodzroa tsi la me be woakpɔ kansa me nugbagbeviwo hã.
8. Ʋudodokpɔwo: Togbɔ be ʋudodokpɔ ɖeɖe mate ŋu akpɔ dzitodzito me kansa o hã la, ate ŋu akpe ɖe ame ŋu wòanya alesi eƒe lãmesẽ le eye wòade dzesi nu manyomanyo ɖesiaɖe si afia be kansa le eŋu.
9. Tsinyegoe ƒe fotoɖeɖe, MRI, PET, kple dodokpɔ bubuwo: Woate ŋu azã dodokpɔ siawo atsɔ akpɔe ɖa be kansa la kaka ɖe ŋutilãa ƒe akpa bubuwo hã.
Ne wokpɔ dzitodzito me kansa ko la, woate ŋu awɔ dodokpɔ bubuwo hã be woanya afisi tututu dɔa ɖo, si akpe ɖe ame ŋu le nyametsotso le dɔdamɔnu si woazã ŋu me.
Dodokpɔ siawo ate ŋu anye esiwo me woazã nutatawo le, abe ahɔhɔ̃ me CT scan, ƒuwo ƒe nutata, alo positron emission tomography (PET) scan ene.
Zhou P, Lu F, Wang J, Wang K, Liu B, Li N, Tang B: A portable point-of-care testing system to diagnose lung cancer through the detection of exosomal miRNA in urine and saliva. Chem Commun (Camb). 2020, 56 (63): 8968-8971.
Ni J, Guo Z, Zhang L: [The diagnostic significance of single or combination lung cancer-related serum biomarkers in high risk lung cancer patients]. Zhonghua Nei Ke Za Zhi. 2016, 55 (1): 25-30.
Nishiyama N, Nakatani S, Iwasa R, Taguchi S, Inoue K, Kinoshita H: [Differential diagnosis between peripheral lung cancer invading the chest wall and chest-wall tumors]. Kyobu Geka. 1997, 50 (10): 893-7.
Kang C, Wang D, Zhang X, Wang L, Wang F, Chen J: Construction and Validation of a Lung Cancer Diagnostic Model Based on 6-Gene Methylation Frequency in Blood, Clinical Features, and Serum Tumor Markers. Comput Math Methods Med. 2021, 2021 (): 9987067.
Heydari F, Rafsanjani MK: A Review on Lung Cancer Diagnosis Using Data Mining Algorithms. Curr Med Imaging. 2021, 17 (1): 16-26.
Li L, Feng T, Zhang W, Gao S, Wang R, Lv W, Zhu T, Yu H, Qian B: MicroRNA Biomarker hsa-miR-195-5p for Detecting the Risk of Lung Cancer. Int J Genomics. 2020, 2020 (): 7415909.
Li B, Yuan Q, Zou YT, Su T, Lin Q, Zhang YQ, Shi WQ, Liang RB, Ge QM, Li QY, Shao Y: CA-125, CA-153, and CYFRA21-1 as clinical indicators in male lung cancer with ocular metastasis. J Cancer. 2020, 11 (10): 2730-2736.
Magee ND, Villaumie JS, Marple ET, Ennis M, Elborn JS, McGarvey JJ: Ex vivo diagnosis of lung cancer using a Raman miniprobe. J Phys Chem B. 2009, 113 (23): 8137-41.
['Mɔxeɖenu: atikewɔwɔ']
['Taɖodzinu siwo nye nufiafia kple nyatakaka koe le nyatakakadzraɖoƒe sia ŋu eye menye atikewɔwɔ ŋuti ɖaŋuɖoɖo alo dɔwɔnawo ƒe nya gblɔm wole o.']
['Mele be woazã nyatakaka siwo wona la atsɔ ada dɔléle alo dɔ aɖe o, eye ele be amesiwo di be yewoakpɔ atikewɔwɔ ŋuti ɖaŋuɖoɖo na yewo la nabia ɖɔkta si xɔ mɔɖegbalẽ.']
['De dzesii be neural network si wɔa nyabiabiawo ƒe ŋuɖoɖowo la meɖia o vevietɔ ne wotsɔ xexlẽdzesiwo wɔe. Le kpɔɖeŋu me, ne wotsɔ ame siwo ŋu dɔléle aɖe le ƒe xexlẽme wɔ dɔe.']
['Bia wò ɖɔkta alo lãmesẽdɔwɔla bubu si dze ƒe aɖaŋuɖoɖo ɣesiaɣi le lãmesẽkuxi aɖe ŋu. Mègaŋe aɖaba ƒu aɖaŋuɖoɖo si ɖɔktawo ɖo na wò alo gbɔ dzi ɖi le exexlẽ me le nyatakakadzraɖoƒe sia ta o. Ne èsusu be ɖewohĩ lãmesẽkuxi aɖe le fu ɖem na ye la, ke yɔ 911 alo yi ɖe afisi wokpɔa nɔnɔme kpatawo gbɔ le.']
['Copyright: Copyright']
['Digital Millennium Copyright Act of 1998, 17 U.S.C. § 512 (the DMCA) na mɔ siwo dzi copyright ƒe nunɔlawo ate ŋu ato awɔ nu ɖe nu siwo wo xɔ se be wo le Internet dzi la ŋu.']
['Ne èxɔe se kple kakaɖedzi be nyatakakadzraɖoƒe alo dɔwɔnu aɖe si míetsɔ wɔ míaƒe nyatakakadzraɖoƒea alo dɔwɔnawo la nye dada le wò gome la, wò ŋutɔ (alo wò dɔtɔ) ate ŋu aŋlɔ agbalẽ aɖo ɖe mí abia be míaɖe nyatakakadzraɖoƒea alo dɔwɔnua ɖa alo axe mɔ ɖe ezazã nu.']
['Ele be woana nyatakakawo to e-mail dzi (kpɔ "Kpekpeɖeŋunaƒe" ƒe akpa si nye e-mail adrɛs). ']
['DMCA bia be nàŋlɔ nyatakaka siwo gbɔna ɖe wò nyatakaka si nèŋlɔ be woada le copyright dzi la me: (1) nuŋɔŋlɔ si fia be copyright le dɔ si ŋu wole nu ƒom le la ŋu; (2) nyatakaka si fia be nuŋɔŋlɔa le eme eye wòade mía nu be míake ɖe eŋu; (3) nyatakaka siwo ana míake ɖe ŋuwò, siwo dometɔ aɖewoe nye wò adrɛs, kaƒodzesi kple e-mail adrɛs; (4) wò nya si fia be èxɔe se kple kakaɖedzi be copyright ƒe ame si tɔe nyatakakaa nye, alo eƒe dɔtɔ, alo se aɖeke meɖe mɔ ɖe eŋu o; ']
['(5) Wò ŋutɔ nàŋlɔ agbalẽ si dzi nàde asii, si me nàde se be ne mèwɔe o la, àda alakpa, atsɔ aɖo kpe edzi be nyatakaka siwo le nyatakakaa me la de pɛpɛpɛ eye be ŋusẽ le asiwò be nàʋli agbalẽ siwo ŋu wogblɔ le be woda le la ta.']
['Eye (6) ame si tɔe agbalẽa nye alo ame si wona ŋusẽe be wòawɔ dɔ le ame si tɔ ŋkɔ me la ƒe asinuŋɔŋlɔ alo eƒe asinuŋɔŋlɔ si le mɔ̃ dzi. ']
['Ne mèŋlɔ nyatakaka siwo katã le etame ɖe agbalẽa me o la, ate ŋu ana be wò nyatoƒoe me dzodzro natsi megbe.']
['Kadodo']
['Taflatse ɖo email ɖe mí ne nyabiabia alo aɖaŋuɖoɖo aɖe le asiwò.']
How is lung cancer diagnosed?
Lung cancer is diagnosed through a combination of tests and procedures, which may include:
1. Medical history and physical examination: The doctor will ask about your symptoms, smoking history, and family history of lung cancer.
They will also perform a physical examination to check for any signs of the disease.
2. Imaging tests: Chest X-rays and computed tomography (CT) scans are commonly used to create detailed images of the lungs and surrounding structures.
These tests can help detect abnormalities, such as tumors or nodules, that may indicate the presence of lung cancer.
3. Sputum cytology: A sample of your sputum (mucus coughed up from the lungs) is examined under a microscope to look for cancer cells.
4. Biopsy: A sample of lung tissue is removed and examined under a microscope to determine if cancer cells are present.
This can be done through a bronchoscopy, needle biopsy, or surgical biopsy.
5. Bronchoscopy: A thin, lighted tube with a camera is inserted through the nose or mouth and down the throat to examine the airways and lungs.
This procedure can also be used to collect tissue samples for biopsy.
6. Fine-needle aspiration (FNA): A thin needle is inserted into the lung nodule or mass to collect a sample of cells for examination.
7. Thoracentesis: Fluid is removed from the space between the lungs and chest wall using a needle, and the fluid is then examined for cancer cells.
8. Blood tests: While blood tests alone cannot diagnose lung cancer, they can help determine the overall health of the patient and identify any abnormalities that may indicate the presence of cancer.
9. Bone scan, mri, pet scan, and other tests: These tests may be used to determine if the cancer has spread to other parts of the body.
Once lung cancer is diagnosed, additional tests may be performed to determine the stage of the cancer, which helps guide treatment decisions.
These tests may include more imaging tests, such as a CT scan of the brain, bone scan, or positron emission tomography (PET) scan.
Disclaimer: medical
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Please note the neural net that generates answers to the questions, is specially inaccurate when it comes to numeric content. For example, the number of people diagnosed with a specific disease.
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Disclaimer: copyright
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['Le Eŋu']
['BioMedLib zãa kɔmpiuta siwo wɔa dɔ le wo ɖokui si (mɔ̃ siwo zãa mɔ̃ɖaŋunuwo tsɔ srɔ̃a nu) tsɔ wɔa nyabiabia kple ŋuɖoɖowo.']
