Tumor definition in medical literature

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Tumor Definition in Medical Literature

Tumor: Abnormal Cell Growth and Mass Formation

In medical literature, a tumor is defined as an abnormal mass of tissue that results from excessive and abnormal cell proliferation. This mass can be either solid or fluid-filled and is also referred to as a "neoplasm" 145. Tumors arise when cells in the body grow and divide uncontrollably, disregarding the normal regulatory mechanisms that keep cell growth in check 145.

Benign vs. Malignant Tumors: Key Differences

Tumors are generally classified into two main types: benign and malignant. Benign tumors are non-cancerous, meaning they remain localized to their site of origin and do not invade surrounding tissues or spread to other parts of the body. Their cells closely resemble normal cells in appearance and behavior 125. In contrast, malignant tumors are cancerous. These tumors are characterized by abnormal cells that grow rapidly, invade nearby tissues, and can spread (metastasize) to distant organs through the blood or lymphatic system 1235. The boundary between malignant tumor cells and normal tissue is often unclear, and these tumors can be life-threatening due to their aggressive nature 235.

Tumor Diagnosis and Classification

To determine whether a tumor is benign or malignant, a biopsy is often performed. In this procedure, a sample of the tumor cells is examined under a microscope by a pathologist . Modern classification systems, such as those used for brain tumors, now incorporate both traditional histopathological features and advanced molecular genetic data, allowing for more precise diagnosis and prognosis .

Tumor Symptoms and Clinical Presentation

Tumors may present with various symptoms depending on their location and type. Common signs include the appearance of a new lump, abnormal bleeding, unexplained weight loss, prolonged cough, or changes in bowel movements. However, these symptoms are not exclusive to tumors and may be caused by other medical conditions .

Advances in Tumor Detection and Research

Recent advances in technology, such as artificial intelligence algorithms, have improved the early detection and classification of tumors. These tools help in diagnosing tumor diseases more accurately and efficiently, which is crucial for timely treatment and better outcomes . Additionally, molecular and genetic research has deepened our understanding of tumor biology and is leading to more personalized treatment approaches, especially in complex cases like brain tumors .

Conclusion

In summary, a tumor is an abnormal mass of tissue caused by uncontrolled cell growth. Tumors can be benign (non-cancerous) or malignant (cancerous), with the latter having the potential to invade and spread throughout the body. Accurate diagnosis, classification, and early detection are essential for effective management and treatment of tumor diseases 12345.

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Most relevant research papers on this topic

Tumors: Benign and Malignant

A tumor can be benign or malignant, depending on the type of cells and their growth patterns.

2018·

34citations

·Tarini Sinha

Cancer Therapy with Common Education

Cancer, characterized by fast growth and unclear boundaries between tumor and normal tissue, can spread to other organs, making it a highly lethal disease.

2017·

0citations

·Gonghuang Cheng

ON CANCER AND TUMOR DISEASES

Cancer is a disease involving abnormal growth with the potential to invade or spread to other parts of the body.

2015·

0citations

·Aseel Mahmood Jawad et al.

Comprehensions keen on the biology of Brain tumors: Possibilities and Challenges

Modern technologies like gene sequencing and personalized medicine are revolutionizing our understanding of brain tumor biology and improving patient survival.

2022·

0citations

·A. H. Habib

Artificial Intellegent algorithms for Tumor Disease Detection: systematic Literature Review

Artificial intelligence algorithms can help detect tumor diseases earlier, potentially reducing the risk of tumor disease and improving cancer diagnosis accuracy.

Systematic Review

2023·

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·Muhammad Hafid Alkarim et al.

SEMANTIC SEGMENTATION BASED CNN FOR TUMOR DETECTION

Deep learning models based on convolutional neural networks and edge detection algorithms can effectively segment tumors in MRI images, improving tumor detection in clinical settings.

2023·

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·V.Parvathi et al.

Dendrimer: An update on recent developments and future opportunities for the brain tumors diagnosis and treatment

Dendrimers effectively diagnose and treat brain tumors by transporting biochemical agents across the blood-brain barrier, offering novel therapeutics like prolonged drug release, immunotherapy, and antineoplastic effects.

Literature Review

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·Monika Kaurav et al.

Collision tumors: A review of their types, pathogenesis, and diagnostic challenges

Collision tumors are rare but significant, and accurate classification and diagnosis can lead to better patient outcomes.

Literature Review

2020·

55citations

·Camille A. Bulte et al.

The power of deep learning for intelligent tumor classification systems: A review

Deep learning techniques show promise in intelligent tumor classification, but require further research and improvements in approach, methods, datasets, and performance metrics for optimal results.

Literature Review

2023·

14citations

·Chandni et al.

A Machine learning based approach for detection of Tumor

The developed machine learning algorithms can accurately detect tumors and classify them as either cancerous or non-cancerous, potentially saving lives.

2021·

0citations

·Kirankumar Madihalli et al.

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