Cancer Ai

Magnetic resonance imaging (MRI) has experienced remarkable advancements in the integration of artificial intelligence (AI) for image acquisition and reconstruction. The availability of raw k-space data is crucial for training AI models in such tasks, but public MRI datasets are mostly restricted to DICOM images only. To address this limitation, the fastMRI initiative released brain and knee k-space datasets, which have since seen vigorous use. In May 2023, fastMRI was expanded to include biparametric (T2- and diffusion-weighted) prostate MRI data from a clinical population...

Given their high affinity and specificity for a range of macromolecules, antibodies are widely used in the treatment of autoimmune diseases, cancers, inflammatory diseases, and Alzheimer's disease (AD). Traditional experimental methods are time-consuming, expensive, and labor-intensive. Recent advances in artificial intelligence (AI) technologies provide complementary methods that can reduce the time and costs required for antibody design by minimizing failures and increasing the success rate of experimental tests...

BACKGROUND: Lynch-like syndrome (LLS) has recently been proposed as a third type of microsatellite instability (MSI) tumor after Lynch syndrome (LS) and sporadic MSI colorectal cancer (CRC) without either a germline variant of mismatch repair (MMR) genes or hypermethylation of the MLH1 gene. The present study aimed to clarify and compare the clinicopathological characteristics of LLS with those of the other MSI CRC subtypes. METHODS: In total, 2634 consecutive patients with CRC who underwent surgical resection and subsequently received universal tumor screening (UTS), including MSI analysis were enrolled between January 2008 and November 2019...

Cancer-associated Fibroblasts (CAFs) exert a tumor-promoting effect in various cancers, including breast cancer. CAFs secrete exosomes containing miRNA and proteins, influencing the tumor microenvironment. In this study, we identified CAF-derived exosomes that transport functional miR-92a from CAFs to tumor cells, thereby intensifying the aggressiveness of breast cancer. CAFs downregulate the expression of G3BP2 in breast cancer cells, and a significant elevation in miR-92a levels in CAF-derived exosomes was observed...

PURPOSE: This review provides an overview of the current state of artificial intelligence (AI) technology for automated detection of breast cancer in digital mammography (DM) and digital breast tomosynthesis (DBT). It aims to discuss the technology, available AI systems, and the challenges faced by AI in breast cancer screening. METHODS: The review examines the development of AI technology in breast cancer detection, focusing on deep learning (DL) techniques and their differences from traditional computer-aided detection (CAD) systems...

BACKGROUND AND AIM: Skin cancer is a major public health issue. While self-examinations and professional screenings are recommended, they are rarely performed. Mobile health (mHealth) apps utilising artificial intelligence (AI) for skin cancer screening offer a potential solution to aid self-examinations; however, their uptake is low. Therefore, the aim of this research was to examine provider and user characteristics influencing people's decisions to seek skin cancer screening performed by a mHealth app or a dermatologist...

PURPOSE: Aromatase Inhibitor-Associated Musculoskeletal Symptoms (AIMSS) are common and frequently lead to AI discontinuation. Single nucleotide polymorphisms (SNPs) in candidate genes have been associated with AIMSS and AI discontinuation. E1Z11 is a prospective cohort study designed to validate associations between 10 SNPs and AI discontinuation due to AIMSS. PATIENTS AND METHODS: Postmenopausal women with stage I-III hormone receptor-positive breast cancer received anastrozole 1 mg daily and completed patient-reported outcomes (PRO) to assess AIMSS (Stanford Health Assessment Questionnaire; HAQ) at baseline, 3, 6, 9, and 12 months...

With the rise of precision medicine, the continuous expansionWith the rise of precision medicine, the continuous expansion the collective push from many other the application of Artificial Intelligence (AI) in prostate cancer diagnosis is increasingly becoming a focal point. AI technology can effectively utilize diverse detection methods such as Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and whole pathology slide imaging to efficiently identify and differentiate between benign and malignant lesions...

OBJECTIVE: Aniline poisoning is considered to be an important factor mediating the development and progression of male bladder cancer,and long non-coding RNA(lncRNA)has also been shown to affect the prognosis of male bladder cancer.Therefore,this study intended to screen and identify lncrnas associated with highly sensitive aniline poisoning of male bladder cancer,and to construct a tumor risk prediction model accordingly. METHODS: Gene expression and clinical data from 410 tissues were downloaded from the Cancer Genome Atlas(TCGA),and all samples were randomly divided into training and testing groups...

Accurate prediction of recurrence and progression in non-muscle invasive bladder cancer (NMIBC) is essential to inform management and eligibility for clinical trials. Despite substantial interest in developing artificial intelligence (AI) applications in NMIBC, their clinical readiness remains unclear. This systematic review aimed to critically appraise AI studies predicting NMIBC outcomes, and to identify common methodological and reporting pitfalls. MEDLINE, EMBASE, Web of Science, and Scopus were searched from inception to February 5th, 2024 for AI studies predicting NMIBC recurrence or progression...

While dual-energy computed tomography (DECT) technology introduces energy-specific information in clinical practice, single-energy CT (SECT) is predominantly used, limiting the number of people who can benefit from DECT. This study proposed a novel method to generate synthetic low-energy virtual monochromatic images at 50 keV (sVMI50keV ) from SECT images using a transformer-based deep learning model, SwinUNETR. Data were obtained from 85 patients who underwent head and neck radiotherapy. Among these, the model was built using data from 70 patients for whom only DECT images were available...

Lymph node metastasis (LNM) detection can be automated using artificial intelligence-based diagnostic tools. Only limited studies have addressed this task for colorectal cancer. The aim of this study was to develop of a clinical-grade digital pathology tool for LNM detection in colorectal cancer (CRC) using the original fast-track framework. The training cohort included 432 slides from one department. A segmentation algorithm detecting 8 relevant tissue classes was trained. The test cohorts consisted of materials from five pathology departments digitized by four different scanning systems...

The novel metal(II)-based complexes HA-Cu, HA-Co, and HA-Ni with phenanthroline, sulfamethazine, and aromatic-aromatic coupled disulfamethazines as ligands were synthesized and characterized. HA-Cu, HA-Co, and HA-Ni all showed a broad spectrum of cytotoxicity and antiangiogenesis. HA-Cu was superior to HA-Co and HA-Ni, and even superior to DDP, showing significant inhibitory effect on the growth and development of tripe-negative breast cancer in vivo and in vitro. HA-Cu exhibited observable synergistic effects of antiproliferation, antiangiogenesis, anti-inflammatory, pro-apoptosis, and cuproptosis to effectively inhibited tumor survival and development...

In recent years, there has been an increase in the interest in adopting Explainable Artificial Intelligence (XAI) for healthcare. The proposed system includes•An XAI model for cancer drug value prediction. The model provides data that is easy to understand and explain, which is critical for medical decision-making. It also produces accurate projections.•A model outperformed existing models due to extensive training and evaluation on a large cancer medication chemical compounds dataset.•Insights into the causation and correlation between the dependent and independent actors in the chemical composition of the cancer cell...

PET scans provide additional clinical value but are costly and not universally accessible. Salehjahromi et al.1 developed an AI-based pipeline to synthesize PET images from diagnostic CT scans, demonstrating its potential clinical utility across various clinical tasks for lung cancer.

PURPOSE: To evaluate the utility of tumor content in circulating cell-free DNA (ccfDNA) for monitoring hepatocellular carcinoma (HCC) throughout its natural history. METHODS: We included 67 hepatitis B virus (HBV)-related HCC patients, of whom 17 had paired pre- and post-treatment samples, and 90 controls. Additionally, in a prospective cohort with HBV surface antigen-positive participants recruited in 2012 and followed up biannually with blood sample collections until 2019, we included 270 repeated samples before diagnosis from 63 participants who later developed HCC (pre-HCC samples)...

Lung adenocarcinoma (LUAD) is the predominant subtype within the spectrum of lung malignancies. CTHRC1 has a pro-oncogenic role in various cancers. Here, we observed the upregulation of CTHRC1 in LUAD, but its role in cisplatin resistance in LUAD remains unclear. Bioinformatics analysis was employed to detect CTHRC1 and SRY-related HMG-box 4 (SOX4) expression in LUAD. Gene Set Enrichment Analysis predicted the enriched pathways related to CTHRC1. JASPAR and MotifMap databases predicted upstream transcription factors of CTHRC1...

BACKGROUND: Endocrine therapy (ET) adherence leads to increased survival in breast cancer (BC). How follow-up should be done to maximize adherence is not known. OBJECTIVES: To assess adherence to ET, factors favouring adherence to ET and effects on survival in a population-based cohort of BC patients in western Sweden. DESIGN: This is a retrospective study. METHODS: We included 358 patients operated for oestrogen receptor-positive BC and recommended 5 years of ET, in Region Halland, Sweden, year 2015 to 2016...

Triple-negative breast cancer (TNBC), the most aggressive subtype of breast cancer, has a poor prognosis and lacks effective treatment strategies. Here, the study discovered that TNBC shows a decreased expression of epithelial transcription factor ovo-like 2 (OVOL2). The loss of OVOL2 promotes fatty acid oxidation (FAO), providing additional energy and NADPH to sustain stemness characteristics, including sphere-forming capacity and tumor initiation. Mechanistically, OVOL2 not only suppressed STAT3 phosphorylation by directly inhibiting JAK transcription but also recruited histone deacetylase 1 (HDAC1) to STAT3, thereby reducing the transcriptional activation of downstream genes carnitine palmitoyltransferase1 (CPT1A and CPT1B)...

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