Retraction: Hussain HM, Hotopf M, Oyebode F. Atypical Antipsychotic Drugs and Alzheimer's Disease. N Engl J Med 2007;356:416.

Hussain, Hadi Meeran

doi:10.1056/nejmc076105

Cited by 12 publications

(4 citation statements)

References 1 publication

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“…Sarma [7] discussed the significance of machine learning algorithms & fraud recognition models in addressing the major challenge of fraud detection in the banking sector. Hussain Mahdi et al [8] emphasized the importance of securing electronic transactions in e-business by utilizing machine learning algorithms to prevent fraud. Ghosh et al's 2023 study focuses on [9] "Water Quality Assessment Through Predictive Machine Learning", highlighting the use of machine learning for analyzing and predicting water quality parameters.…”

Section: Literature Reviewmentioning

confidence: 99%

Credit Card Deception Recognition Using Random Forest Machine Learning Algorithm

Jaiswal,

Bharadwaj,

Kumari

et al. 2024

EAI Endorsed Trans IoT

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INTRODUCTION: The credit card deception poses a global threat, resulting in significant monetary losses and identity theft. Detecting fraudulent transactions promptly is crucial for mitigating these losses. Machine learning algorithms, specifically the random forest algorithm, show promise in addressing this issue. OBJECTIVES: This research paper presents a comprehensive study of numerous machine learning algorithms for credit card deception recognition, focusing on the random forest algorithm. METHODS: To tackle the increasing fraud challenges and the need for more effective detection systems, we develop an advanced credit card deception detection system utilizing machine learning algorithms. We evaluate our system's performance using precision, recall, & F1-score metrics. Additionally, we provide various insights into the key features for fraud detection, empowering financial institutions to enhance their detection systems. The paper follows a structured approach. RESULTS: We review existing work on credit card fraud detection, detail the dataset and pre-processing steps, present the random forest algorithm and its application to fraud detection, compare its performance against other algorithms, discuss fraud detection challenges, and propose effective solutions. CONCLUSION: Finally, we conclude the research paper and suggest potential areas for future research. Our experiments demonstrate that the random forest algorithm surpasses other machine learning algorithms in accuracy, precision, recall, & F1-score. Moreover, the system effectively addresses challenges like imbalanced data and high-dimensional feature spaces. Our findings offer valuable insights into the most relevant features for fraud detection empowering financial organizations to improve their fraud detection capabilities.

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Section: Literature Reviewmentioning

confidence: 99%

Credit Card Deception Recognition Using Random Forest Machine Learning Algorithm

Jaiswal,

Bharadwaj,

Kumari

et al. 2024

EAI Endorsed Trans IoT

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“…Among its molecular targets are transcription factors, growth factors and their receptors, cytokines, enzymes, and genes regulating cell proliferation and apoptosis. Extensive investigation suggests that curcumin has therapeutic potential in the treatment of various disorders (Scheme 1) as it is known to reduce blood cholesterol, [80][81][82][83][84][85] prevent low-density lipoprotein oxidation, [86][87][88] inhibit platelet aggregation, 89,90 suppress thrombosis 91,92 and myocardial infarction, [93][94][95][96] suppress symptoms associated with type II diabetes, [97][98][99][100][101][102][103][104] rheumatoid arthritis, [105][106][107][108][109] multiple sclerosis 110 and Alzheimer's disease, [111][112][113][114][115] inhibits HIV replication, [116][117][118][119][120][121][122][123][124] enhance wound heali...…”

Section: Curcumin Against Cancermentioning

confidence: 99%

Synthetic strategies in curcumin chemistry focused on anticancer applications

Theppawong¹,

Kaur²,

Kumar³

et al. 2020

Arkivoc

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In spite of having received considerable interest as a potential anticancer agent over the past two decades, curcumin has not been developed into a sturdy drug candidate yet, mainly due to the challenges imposed by its rapidly metabolizable structure, leading to bioavailability and stability issues, and its aspecific activity. To circumvent these obstacles, chemical modification of the parent scaffold has been shown to involve an eligible approach for the construction of curcuminoids with improved properties. This review article provides a compilation of curcumin modifications and the effect thereof on the anticancer activity displayed by the resulting new analogs.

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“…[14,15] In particular, there is a need for technologies capable of collecting sweat volumes that are adequate for analysis, and methods to securely store sweat in selective channels or chambers to prevent evaporation and cross contamination. [16] Since sweat is produced by eccrine glands in nearly every part of human skin, it is particularly conducive to wearable and continuous monitoring. Continuous skin-integrated sweat sensing for both sweat rate and biomarker analysis presents its own unique set of challenges particularly in use cases such as intense exercise or military applications.…”

Section: Introductionmentioning

confidence: 99%

“…Although recent advances have demonstrated the feasibility of collecting and analyzing sweat in real time, numerous technical challenges still remain . In particular, there is a need for technologies capable of collecting sweat volumes that are adequate for analysis, and methods to securely store sweat in selective channels or chambers to prevent evaporation and cross contamination …”

Section: Introductionmentioning

confidence: 99%

Super‐Absorbent Polymer Valves and Colorimetric Chemistries for Time‐Sequenced Discrete Sampling and Chloride Analysis of Sweat via Skin‐Mounted Soft Microfluidics

Kim

Zhang

Won

et al. 2018

Small

124

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This paper introduces super absorbent polymer valves and colorimetric sensing reagents as enabling components of soft, skin-mounted microfluidic devices designed to capture, store, and chemically analyze sweat released from eccrine glands. The valving technology enables robust means for guiding the flow of sweat from an inlet location into a collection of isolated reservoirs, in a well-defined sequence. Analysis in these reservoirs involves a color responsive indicator of chloride concentration with a formulation tailored to offer stable operation with sensitivity optimized for the relevant physiological range. Evaluations on human subjects with comparisons against ex situ analysis illustrate the practical utility of these advances.

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Retraction: Hussain HM, Hotopf M, Oyebode F. Atypical Antipsychotic Drugs and Alzheimer's Disease. N Engl J Med 2007;356:416.

Cited by 12 publications

References 1 publication

Credit Card Deception Recognition Using Random Forest Machine Learning Algorithm

Credit Card Deception Recognition Using Random Forest Machine Learning Algorithm

Synthetic strategies in curcumin chemistry focused on anticancer applications

Super‐Absorbent Polymer Valves and Colorimetric Chemistries for Time‐Sequenced Discrete Sampling and Chloride Analysis of Sweat via Skin‐Mounted Soft Microfluidics

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