Application of artificial intelligence in the diagnosis, treatment, and recurrence prediction of peritoneal carcinomatosis

Heliyon, Journal Year: 2024, Volume and Issue: 10(7), P. e29249 - e29249

Published: April 1, 2024

Peritoneal carcinomatosis (PC) is a type of secondary cancer which not sensitive to conventional intravenous chemotherapy. Treatment strategies for PC are usually palliative rather than curative. Recently, artificial intelligence (AI) has been widely used in the medical field, making early diagnosis, individualized treatment, and accurate prognostic evaluation various cancers, including mediastinal malignancies, colorectal cancer, lung more feasible. As branch computer science, AI specializes image recognition, speech automatic large-scale data extraction output. technologies have also made breakthrough progress field peritoneal based on its powerful learning capacity efficient computational power. successfully applied approaches imaging, blood tests, proteomics, pathological diagnosis. Due function convolutional neural network model machine algorithms, AI-assisted diagnosis types associated with higher accuracy rate compared methods. In addition, treatment surgical resection, intraperitoneal chemotherapy, systemic significantly improves survival patients PC. particular, recurrence prediction emotion combined technology, further improving quality life patients. Here we comprehensively reviewed summarized latest developments application PC, helping oncologists diagnose provide precise

Language: Английский

The effect of COVID-19 on cancer incidences in the U.S

Heliyon, Journal Year: 2024, Volume and Issue: 10(7), P. e28804 - e28804

Published: March 30, 2024

Fundamental data analysis assists in the evaluation of critical questions to discern essential facts and elicit formerly invisible evidence. In this article, we provide clarity into a subtle phenomenon observed cancer incidences throughout time COVID-19 pandemic. We analyzed incidence from American Cancer Society [1]. partitioned three groups: pre-COVID-19 years (2017, 2018), during (2019, 2020, 2021), post-COVID-19 (2022, 2023). novel manner, applied principal components (PCA), computed angles between vectors, then added lognormal probability concepts our analysis. Our analytic results revealed that shifted within each era (pre, during, post), with meaningful change occurring peak era. defined, computed, interpreted exceedance for type have 1000 future year among breast, cervical, colorectal, uterine corpus, leukemia, lung & bronchus, melanoma, Hodgkin's lymphoma, prostate, urinary cancers. also estimated, illustrated indices other diagnoses vantage point breast pre, eras. The angle vectors post were 72% less than pre-pandemic 28% movement was dynamic these eras, greatly differed by cancer. A trend chart cervical showed statistical anomalies 2019 2021. Based on findings, few research directions are pointed out.

Language: Английский