Application of frequency characteristic extraction in increasing the accuracy of X-ray based thickness gauges used for aluminum alloys employing GMDH neural network.

Radiation-based gauges have been widely utilized in the industry as a dependable, non-destructive method of measuring metal layer thickness. It is only possible to trust the conventional radiation thickness meter when the material's composition is known in advance. Thickness measurement errors are to be anticipated in contexts like rolled metal factories, where the real component of the material could diverge greatly from the stated composition. An X-ray-based device was suggested in this study to measure aluminum sheet thickness and identify the type of its alloys. Transmission and backscattered X-ray energy were recorded using two sodium iodide detectors while a 150 kV X-ray tube in the described detection system was operated. Aluminum layers of varying thicknesses (2-45 mm) and alloys (1050, 3105, 5052, and 6061) were simulated to be placed between the X-ray source and the transmission detector. The development of radiation-based systems used the MCNP code as a very powerful framework to imitate the detecting architecture and the spectra acquired by the detectors. The recorded signals were transferred to the frequency domain using the Fourier transform, and the frequency characteristics were extracted from them. Two GMDH neural networks were trained using these characteristics: one to identify the alloy type and another to determine the aluminum layer's thickness. The classifier network had a 92.2% success rate in identifying the alloy type, while the predictive network had a 1.9% error rate in determining the thickness of the aluminum layer. By extracting important characteristics and using powerful neural networks, this study was able to improve the precision with which aluminum layer thickness was measured and correctly identify the alloy type. The suggested method is used to determine the thickness of aluminum and its alloy sheets and may also be applied to other metals.

Genetic diversity and antagonistic properties of Trichoderma strains from the crop rhizospheres in southern Rajasthan, India.

There are fewer studies on Trichoderma diversity in agricultural fields. The rhizosphere of 16 crops was analyzed for Trichoderma species in 7 districts of Rajasthan state of India. Based on DNA sequence of translation elongation factor 1α (tef-1α), and morphological characteristics, 60 isolates were identified as 11 species: Trichoderma brevicompactum, species in Harzianum clade identified as T. afroharzianum, T. inhamatum, T. lentiforme, T. camerunense, T. asperellum, T. asperelloides, T. erinaceum, T. atroviride, T. ghanense, and T. longibrachiatum. T. brevicompactum is the most commonly occurring strain followed by T. afroharzianum. No new species were described in this study. T. lentiforme, showed its first occurrence outside the South American continent. The morphological and cultural characteristics of the major species were observed, described, and illustrated in detail. The isolates were tested for their antagonistic effect against three soilborne plant pathogens fungi: Sclerotium rolfsii, Rhizoctonia solani, and Fusarium verticillioides in plate culture assays. One of the most potent strains was T. afroharzianum BThr29 having a maximum in vitro inhibition of S. rolfsii (76.6%), R. solani (84.8%), and F. verticillioides (85.7%). The potential strain T. afroharzianum BThr29 was also found to be efficient antagonists against soil borne pathogens in in vivo experiment. Such information on crop selectivity, antagonistic properties, and geographic distribution of Trichoderma species will be beneficial for developing efficient Trichoderma-based biocontrol agents.

The value of high-risk clinicopathologic features for chemotherapy in stage I non-small cell lung cancer: a propensity score-matched study.

Background: Surgical resection is the main treatment for early-stage non-small cell lung cancer (NSCLC), but recurrence remains a concern. Adjuvant chemotherapy has been shown to have survival benefits for resected stage II and III NSCLC, but debate continues regarding its use in stage I NSCLC. High-risk features, such as tumor size and stage, are considered in deciding whether to administer adjuvant chemotherapy. Methods: The data of 666,689 patients diagnosed with lung cancer from 2004 to 2016 were collected from the Surveillance, Epidemiology, and End Results database. Ultimately, 26,160 patients diagnosed with stage I NSCLC were included in the study based on a screening procedure. Results: After matching, 4,285 patients were identified, of whom 1,440 (33.6%) received chemotherapy. High-risk clinicopathologic features, including a high histologic grade, visceral pleural invasion (VPI), the examination of an insufficient number of lymph nodes (LNs), and limited resection, were independent risk factors for a poor prognosis. Chemotherapy significantly improved lung cancer-specific survival (LCSS) and overall survival (OS) in stage I patients with VPI [LCSS: hazard ratio (HR): 0.839, 95% confidence interval (CI): 0.706-0.998, P=0.047; OS: HR: 0.711, 95% CI: 0.612-0.826, P<0.001], regardless of whether or not the patient had fewer than 11 LNs (LCSS: HR: 0.809, 95% CI: 0.664-0.986, P=0.04; OS: HR: 0.677, 95% CI: 0.570-0.803, P<0.001). Chemotherapy was only observed to improve OS for stage IB patients with a high histologic grade when combined with either or both of the following high-risk factors: the presence of VPI and fewer than 11 LNs examined. Conclusions: The presence of VPI was the dominant predictor and the examination of an insufficient number of LNs was the secondary indicator, and a high histologic grade was a potential indicator of the need to administer chemotherapy in the treatment of stage I NSCLC.

Change in quality of life of stage IA non-small cell lung cancer after surgery or radiation therapy.

Background: Few studies have examined the differential impact of stereotactic body radiotherapy (SBRT) and surgery for early-stage non-small cell lung cancer (NSCLC) on quality of life (QoL) during the first post-treatment year. Methods: A prospective cohort of stage IA NSCLC patients undergoing surgery or SBRT at Mount Sinai Health System had QoL measured before treatment, and 2, 6, and 12 months post-treatment using: 12-item Short Form Health Survey version 2 (SF-12v2) [physical component summary (PCS) and mental component summary (MCS)], Functional Assessment of Cancer Therapy-Lung Cancer Subscale (FACT-LCS), and the Patient Health Questionnaire-4 (PHQ-4) measuring depression and anxiety. Locally weighted scatterplot smoothing (LOWESS) was fitted to identify the best interval knot for the change in the QoL trends post-treatment, adjusted piecewise linear mixed effects model was developed to estimate differences in baseline, 2- and 12-month scores, and rates of change. Results: In total, 503 (88.6%) patients received surgery and 65 (11.4%) SBRT. LOWESS plots suggested QoL changed at 2 months post-surgery. Worsening in PCS was observed for both surgery and SBRT within 2 months after treatment but was only significant for surgical patients (-2.11, P<0.001). Two months later, improvements were observed for surgical but not SBRT patients (0.63 vs. -0.30, P<0.001). Surgical patients had significantly better PCS (P<0.001) and FACT-LCS (P<0.001) scores 1-year post-treatment compared to baseline, but not SBRT patients. Both surgical and SBRT patients reported significantly less anxiety 1-year post-treatment compared to baseline (P<0.001 and P=0.03). Decrease in depression from baseline to 1-year post-treatment was only significant for surgical patients (P<0.001). Conclusions: Post-treatment, surgical patients exhibited improvements in physical health and reductions in lung cancer symptoms following initial deterioration within the first two months; in contrast, SBRT patients showed persistent decline in these areas throughout the year. Nonetheless, improved mental health was noted across both patient categories post-treatment. Targeted interventions and continuous monitoring are recommended during the initial 2 months post-surgery and throughout the year post-SBRT to alleviate physical and mental distress in patients.

Synthesis, spectroscopic, chemical reactivity, topology analysis and molecular docking study of ethyl 5-hydroxy-2-thioxo-4-(p-tolyl)-6-(trifluoromethyl)hexahydropyrimidine-5-carboxylate.

The organofluorine hexahydropyrimidine derivatives are used in the drug discovery due to its steric nature to hydrogen and its extreme electronegativity. The Ethyl 5-hydroxy-2-thioxo-4-(p-tolyl)-6-(trifluoromethyl)hexahydropyrimidine-5-carboxylate (ETP5C) compound was synthesized and characterized by NMR (13C and 1H), FT-IR and UV-Vis spectroscopic techniques for experimentally and theoretically and elemental analyses, mass spectra also investigated. The most stable structure of synthesized molecule was studied by PES analysis in gas and liquid medium. The structural parameters such as bond length and bond angle of the title molecule have been obtained by DFT/B3LYP/6-311++G (d,p) set and compared with the structurally related experimental data of the compounds. The π-to-π* transition of the ETP5C molecule is identified using UV-Vis absorption spectral analysis. In addition, the chemical stability and reactivity are investigated using HOMO-LUMO analysis. The minimal HOMO-LUMO energy gap (4.6255 eV) clearly explains that the ETP5C molecule is more reactive for receptors. The nucleophilic and electrophilic regions such as active sites have been shown by MEP, ELF, LOL and Fukui functions. The second order optical effect has been explained by NLO analysis. The docking was performed with antineoplastic proteins that exhibit against the development of tumor cells.

Prospective Cohort Study to Compare Long-Term Lung Cancer-Specific and All-Cause Survival of Clinical Early Stage (T1a-b; ≤20 mm) NSCLC Treated by Stereotactic Body Radiation Therapy and Surgery.

INTRODUCTION: We aimed to compare outcomes of patients with first primary clinical T1a-bN0M0 NSCLC treated with surgery or stereotactic body radiation therapy (SBRT). METHODS: We identified patients with first primary clinical T1a-bN0M0 NSCLCs on last pretreatment computed tomography treated by surgery or SBRT in the following two prospective cohorts: International Early Lung Cancer Action Program (I-ELCAP) and Initiative for Early Lung Cancer Research on Treatment (IELCART). Lung cancer-specific survival and all-cause survival after diagnosis were compared using Kaplan-Meier analysis. Propensity score matching was used to balance baseline demographics and comorbidities and analyzed using Cox proportional hazards regression. RESULTS: Of 1115 patients with NSCLC, 1003 had surgery and 112 had SBRT; 525 in I-ELCAP in 1992 to 2021 and 590 in IELCART in 2016 to 2021. Median follow-up was 57.6 months. Ten-year lung cancer-specific survival was not significantly different: 90% (95% confidence interval: 87%-92%) for surgery versus 88% (95% confidence interval: 77%-99%) for SBRT, p = 0.55. Cox regression revealed no significant difference in lung cancer-specific survival for the combined cohorts (p = 0.48) or separately for I-ELCAP (p = 1.00) and IELCART (p = 1.00). Although 10-year all-cause survival was significantly different (75% versus 45%, p < 0.0001), after propensity score matching, all-cause survival using Cox regression was no longer different for the combined cohorts (p = 0.74) or separately for I-ELCAP (p = 1.00) and IELCART (p = 0.62). CONCLUSIONS: This first prospectively collected cohort analysis of long-term survival of small, early NSCLCs revealed that lung cancer-specific survival was high for both treatments and not significantly different (p = 0.48) and that all-cause survival after propensity matching was not significantly different (p = 0.74). This supports SBRT as an alternative treatment option for small, early NSCLCs which is especially important with their increasing frequency owing to low-dose computed tomography screening. Furthermore, treatment decisions are influenced by many different factors and should be personalized on the basis of the unique circumstances of each patient.

A 20-year Follow-up of the International Early Lung Cancer Action Program (I-ELCAP).

Background The low-dose CT (≤3 mGy) screening report of 1000 Early Lung Cancer Action Program (ELCAP) participants in 1999 led to the International ELCAP (I-ELCAP) collaboration, which enrolled 31 567 participants in annual low-dose CT screening between 1992 and 2005. In 2006, I-ELCAP investigators reported the 10-year lung cancer-specific survival of 80% for 484 participants diagnosed with a first primary lung cancer through annual screening, with a high frequency of clinical stage I lung cancer (85%). Purpose To update the cure rate by determining the 20-year lung cancer-specific survival of participants diagnosed with first primary lung cancer through annual low-dose CT screening in the expanded I-ELCAP cohort. Materials and Methods For participants enrolled in the HIPAA-compliant prospective I-ELCAP cohort between 1992 and 2022 and observed until December 30, 2022, Kaplan-Meier survival analysis was used to determine the 10- and 20-year lung cancer-specific survival of participants diagnosed with first primary lung cancer through annual low-dose CT screening. Eligible participants were aged at least 40 years and had current or former cigarette use or had never smoked but had been exposed to secondhand tobacco smoke. Results Among 89 404 I-ELCAP participants, 1257 (1.4%) were diagnosed with a first primary lung cancer (684 male, 573 female; median age, 66 years; IQR, 61-72), with a median smoking history of 43.0 pack-years (IQR, 29.0-60.0). Median follow-up duration was 105 months (IQR, 41-182). The frequency of clinical stage I at pretreatment CT was 81% (1017 of 1257). The 10-year lung cancer-specific survival of 1257 participants was 81% (95% CI: 79, 84) and the 20-year lung cancer-specific survival was 81% (95% CI: 78, 83), and it was 95% (95% CI: 91, 98) for 181 participants with pathologic T1aN0M0 lung cancer. Conclusion The 10-year lung cancer-specific survival of 80% reported in 2006 for I-ELCAP participants enrolled in annual low-dose CT screening and diagnosed with a first primary lung cancer has persisted, as shown by the updated 20-year lung cancer-specific survival for the expanded I-ELCAP cohort. © RSNA, 2023 See also the editorials by Grenier and by Sequist and Olazagasti in this issue.

Fat mass: a novel digital biomarker for remote monitoring that may indicate risk for malnutrition and new complications in decompensated cirrhosis.

BACKGROUND: Cirrhosis is associated with sarcopaenia and fat wasting, which drive decompensation and mortality. Currently, nutritional status, through body composition assessment, is not routinely monitored in outpatients. Given the deleterious outcomes associated with poor nutrition in decompensated cirrhosis, there is a need for remotely monitoring this to optimise community care. METHODS: A retrospective analysis was conducted on patients monitored remotely with digital sensors post hospital discharge, to assess outcomes and indicators of new cirrhosis complications. 15 patients had daily fat mass measurements as part of monitoring over a median 10 weeks, using a Withing's bioimpedance scale. The Clinical Frailty Score (CFS) was used to assess frailty and several liver disease severity scores were assessed. RESULTS: 73.3% (11/15) patients were male with a median age of 63 (52-68). There was a trend towards more severe liver disease based on CLIF-Consortium Acute Decompensation (CLIF-C AD) scores in frail patients vs. those not frail (53 vs 46, p = 0.072). When the cohort was split into patients who gained fat mass over 8 weeks vs. those that lost fat mass, the baseline CLIF-C AD scores and WBC were significantly higher in those that lost fat (58 vs 48, p = 0.048 and 11.2 × 109 vs 4.7 × 109, p = 0.031). CONCLUSIONS: This proof-of-principle study shows feasibility for remote monitoring of fat mass and nutritional reserve in decompensated cirrhosis. Our results suggest fat mass is associated with greater severity of acute decompensation and may serve as an indicator of systemic inflammatory response. Further prospective studies are required to validate this digital biomarker.

Characterization of bioactive compound isolated from Micromonospora marina KPMS1 and its activity against emerging antibiotics resistant strains of Klebsiella pneumoniae HAUTI7 and Proteus vulgaris HAUTI14.

Multiple antibiotic resistances have increased gradually in many classes of antibiotics among the gram negative organisms like Klebsiella pneumoniae and Proteus vulgaris which are the major causes of infection among worldwide. Nearly a hundred urine samples were collected, among them 16 urine samples were having plasmid and its resistant to various antibiotics. This present investigation has determined the resistant plasmid pattern of multi drug resistant Klebsiella pneumoniae and Proteus vulgaris from urinary tract site isolated from hospital patients. The detection and characterization of antimicrobial metabolite derived from marine sediments that produce potent activity against multidrug resistant pathogen. The 16S rRNA sequencing results and phylogeny showed that the resistant bacteria belong to the genera of Klebsiella pneumoniae HAUTI7 and Proteus vulgaris HAUTI14. The antibacterial activity and the characterization of bioactive compound like FT-IR and NMR studies were performed to analyze the structural elucidation of active compounds derived from marine source Micromonospora marina KPMS1. The 16S rRNA sequences of Micromonospora marina KPMS1was deposited in the Gen bank with the accession number MH036351. The effective bioactive compound derived from marine sediments are virtually unlimited interest that control the emerging multiple antibiotic resistant strains.

Intelligent Measuring of the Volume Fraction Considering Temperature Changes and Independent Pressure Variations for a Two-Phase Homogeneous Fluid Using an 8-Electrode Sensor and an ANN.

Two-phase fluids are widely utilized in some industries, such as petrochemical, oil, water, and so on. Each phase, liquid and gas, needs to be measured. The measuring of the void fraction is vital in many industries because there are many two-phase fluids with a wide variety of liquids. A number of methods exist for measuring the void fraction, and the most popular is capacitance-based sensors. Aside from being easy to use, the capacitance-based sensor does not need any separation or interruption to measure the void fraction. In addition, in the contemporary era, thanks to Artificial Neural Networks (ANN), measurement methods have become much more accurate. The same can be said for capacitance-based sensors. In this paper, a new metering system utilizing an 8-electrode sensor and a Multilayer Perceptron network (MLP) is presented to predict an air and water volume fractions in a homogeneous fluid. Some characteristics, such as temperature, pressure, etc., can have an impact on the results obtained from the aforementioned sensor. Thus, considering temperature changes, the proposed network predicts the void fraction independent of pressure variations. All simulations were performed using the COMSOL Multiphysics software for temperature changes from 275 to 370 degrees Kelvin. In addition, a range of 1 to 500 Bars, was considered for the pressure. The proposed network has inputs obtained from the mentioned software, along with the temperature. The only output belongs to the predicted void fraction, which has a low MAE equal to 0.38. Thus, based on the obtained result, it can be said that the proposed network precisely measures the amount of the void fraction.

An overview of polymer surface coated synthetic quantum dots as therapeutics and sensors applications.

Quantum dots (QDs) are a class of remarkable materials that have garnered significant attention since their initial discovery. It is noteworthy to mention that it took approximately a decade for these materials to be successfully implemented in practical applications. While QDs have demonstrated notable optical properties, it is important to note that these attributes alone have not rendered them a feasible substitute for traditional organic dyes. Furthermore, it is worth noting that the substance under investigation exhibited inherent toxicity and instability in its initial state, primarily due to the presence of a heavy metal core. In the initial stages of research, it was observed that the integration of nanocomposites had a positive impact on the properties of QDs. The discovery of these nanocomposites was motivated by the remarkable properties exhibited by biocomposites found in nature. Recent discoveries have shed light on the potential utilization of QDs as a viable strategy for drug delivery, offering a promising avenue to enhance the efficacy of current pharmaceuticals and pave the way for the creation of innovative therapeutic approaches. The primary objective of this review was to elucidate the distinctive characteristics that render QDs highly suitable for utilization as nanocarriers. In this study, we will delve into the multifaceted applications of QDs as sensing nanoprobes and their utilization in diverse drug delivery systems. The focus of our investigation was directed toward the utilization of QD/polymer composites in sensing applications, with particular emphasis on their potential as chemical sensors, biosensors, and physical sensors.

Unequal racial distribution of immunotherapy for late-stage non-small cell lung cancer.

Immunotherapy has increased survival for non-small cell lung cancer (NSCLC), especially for those diagnosed with late-stage disease. However, it is not known if its use is equally distributed across races. We assessed immunotherapy use in 21 098 pathologically confirmed stage IV NSCLC patients according to race in the Surveillance Epidemiology, and End Results-Medicare linked dataset. Multivariable models were conducted to evaluate the independent association of receipt of immunotherapy with race and overall survival according to race. Black patients had statistically significantly lower odds of receiving immunotherapy (adjusted odds ratio = 0.60, 95% confidence interval = 0.44 to 0.80); receipt of immunotherapy was lower in Asian and Hispanic patients but not statistically significant. When immunotherapy was received, survival was similar across races. Immunotherapy for NSCLC is not used equally among races, underscoring the racial disparities that exist in access to the newest cancer treatment. Efforts should be directed toward expanding access to novel, efficacious treatments for advanced stage lung cancer.

Drug target of natural products and COVID-19: how far has science progressed?

The new coronavirus [severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)] that caused a viral disease with a high risk of mortality (coronavirus disease 2019) was found toward the end of 2019. This was a significant acute respiratory syndrome. In a brief period, this virus spread throughout the entire planet, causing tremendous loss of life and economic damage. The process of developing new treatments takes time, and there are presently no recognized specific treatments to treat this infection. The most promising participants, who subsequently developed into prospective leads, were dropped from the clinical research in their latter phases. Medication that has previously acquired permission may only be repurposed for use for various medical reasons following a thorough investigation for safety and effectiveness. Because there are now no effective treatments available, natural products are being used haphazardly as antiviral medications and immunity boosters. The fundamental statement that most natural compounds have powerful antiviral action does not apply to SARS-CoV-2. Middle East respiratory syndrome coronavirus and severe acute respiratory syndrome coronavirus infections are inhibited by natural treatments. According to an in silico study, the virus' nonstructural proteins, including PLpro, Mpro, and RdRp, as well as structural proteins like the spike (S) protein, have been shown to have a strong affinity for several natural products and to be inhibited by them. The virus also suggests that it is a valid candidate for therapeutic research since it utilizes the intracellular angiotensin-converting enzyme 2 receptor of the host cell. In this study, interesting targets for SARS-CoV-2 medication development are explored, as well as the antiviral properties of some well-known natural compounds.

Isolation, identification, and screening of biosurfactant-producing and hydrocarbon-degrading bacteria from oil and gas industrial waste.

Qatar is one of the biggest oil and gas producers in the world, coupled with it is challenging environmental conditions (high average temperature: >40 °C, low annual rainfall: 46.71 mm, and high annual evaporation rate: 2200 mm) harbors diverse microbial communities that are novel and robust, with the potential to biodegrade hydrocarbons. In this study, we collected hydrocarbon contaminated sludge, wastewater and soil samples from oil and gas industries in Qatar. Twenty-six bacterial strains were isolated in the laboratory from these samples using high saline conditions and crude oil as the sole carbon source. A total of 15 different bacterial genera were identified in our study that have not been widely reported in the literature or studied for their usage in the biodegradation of hydrocarbons. Interestingly, some of the bacteria that were identified belonged to the same genus however, demonstrated variable growth rates and biosurfactant production. This indicates the possibility of niche specialization and specific evolution to acquire competitive traits for better survival. The most potent strain EXS14, identified as Marinobacter sp., showed the highest growth rate in the oil-containing medium as well as the highest biosurfactant production. When this strain was further tested for biodegradation of hydrocarbons, the results showed that it was able to degrade 90 to 100% of low and medium molecular weight hydrocarbons and 60 to 80% of high molecular weight (C35 to C50) hydrocarbons. This study offers many promising leads for future studies of microbial species and their application for the treatment of hydrocarbon contaminated wastewater and soil in the region and in other areas with similar environmental conditions.

Artificial Intelligence: A Next-Level Approach in Confronting the COVID-19 Pandemic.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which caused coronavirus diseases (COVID-19) in late 2019 in China created a devastating economical loss and loss of human lives. To date, 11 variants have been identified with minimum to maximum severity of infection and surges in cases. Bacterial co-infection/secondary infection is identified during viral respiratory infection, which is a vital reason for morbidity and mortality. The occurrence of secondary infections is an additional burden to the healthcare system; therefore, the quick diagnosis of both COVID-19 and secondary infections will reduce work pressure on healthcare workers. Therefore, well-established support from Artificial Intelligence (AI) could reduce the stress in healthcare and even help in creating novel products to defend against the coronavirus. AI is one of the rapidly growing fields with numerous applications for the healthcare sector. The present review aims to access the recent literature on the role of AI and how its subfamily machine learning (ML) and deep learning (DL) are used to curb the pandemic's effects. We discuss the role of AI in COVID-19 infections, the detection of secondary infections, technology-assisted protection from COVID-19, global laws and regulations on AI, and the impact of the pandemic on public life.

Corrigendum to 'Point-of-care viscoelastic testing' [BJA Education 22 (2022) 416-423].

[This corrects the article DOI: 10.1016/j.bjae.2022.07.003.].

Applications of Neural Network-Based Plan-Cancer Method for Primary Diagnosis of Mesothelioma Cancer.

"Malignant mesothelioma (MM)" is an uncommon although fatal form of cancer. The proper MM diagnosis is crucial for efficient therapy and has significant medicolegal implications. Asbestos is a carcinogenic material that poses a health risk to humans. One of the most severe types of cancer induced by asbestos is "malignant mesothelioma." Prolonged shortness of breath and continuous pain are the most typical symptoms of the condition. The importance of early treatment and diagnosis cannot be overstated. The combination "epithelial/mesenchymal appearance of MM," however, makes a definite diagnosis difficult. This study is aimed at developing a deep learning system for medical diagnosis MM automatically. Otherwise, the sickness might cause patients to succumb to death in a short amount of time. Various forms of artificial intelligence algorithms for successful "Malignant Mesothelioma illness" identification are explored in this research. In relation to the concept of traditional machine learning, the techniques support "Vector Machine, Neural Network, and Decision Tree" are chosen. SPSS has been used to analyze the result regarding the applications of Neural Network helps to diagnose MM.

Modifications to rapid response team (medical emergency team) activation criteria and its impact on patient safety.

BACKGROUND: Modifications to rapid response team (RRT) activation criteria occur commonly in Australian hospitals without evidence to define their use. AIMS: To evaluate the effectiveness of RRT activation criteria modifications in preventing RRT activation and differences in adverse events associated with treatment delays caused by modifications. METHODS: A prospective chart audit of hospital patients with RRT activation criteria modifications admitted during a 12-month period in a large regional hospital in Toowoomba, Australia. The incidence of RRT activation criteria modifications, RRT activations and rates of adverse events following criteria modifications were investigated. Adverse events were defined as a delayed treatment on the ward, unplanned intensive care unit admission, cardiac arrest and unexpected death. Differences in patient outcomes among medical and surgical patients were also investigated. RESULTS: A total of 271 patients out of 4009 admitted patients had modifications to their RRT activation criteria. There was no difference in rates of RRT activation in patients with modified criteria compared with patients with unmodified criteria (P = 0.37). In patients with RRT activation criteria modifications, rates of adverse events were higher in patients who met their modified RRT criteria (93.3%) compared with those who did not meet modified RRT criteria (3.8%; P < 0.001). Additionally, in patients with modifications, rates of adverse events were higher in medical patients (27.6%; n = 50) compared with surgical patients (15.6%; n = 14; P = 0.03). CONCLUSIONS: The results strongly suggest that RRT criteria modification is associated with no difference in rates of RRT activation and with detrimental impacts on patient safety, particularly in medical patients.

Temozolomide-induced vitiligo-like reaction: An extremely rare phenomenon.

ABSTRACT: Temozolomide (TMZ) is an alkylating chemotherapeutic drug, often used in high-grade glioma and metastatic melanoma. Common side effects of this include myelosuppression and gastrointestinal side effects. Vitiligo-like reaction is extremely rare after TMZ. Here, we report a case of a 55-year-old patient of glioblastoma who developed vitiligo-like reaction after starting adjuvant TMZ.