Title: Detecting False Positives with Derived Planetary Parameters: Experimenting With The KEPLER Dataset

Authors: Ayan Bin Rafaih, Zachary Murray

Journal: Under peer-review in Open Journal of Astrophysics

Year: 2025

Abstract:

Recent developments in computational power and machine learning techniques motivate their use in many different astrophysical research areas. Consequently, many machine learning models have been trained to classify exoplanet transit signals – typically done by using time series light curves. In this work, we attempt a different approach and try to improve the efficiency of these algorithms by fitting only derived planetary parameters, instead of full time-series light curves. We investigate and evaluate 4 models (Logistic Regression, Random Forest, Support Vector Machines, and Convolutional Neural Networks) on the KEPLER dataset, using precision-recall trade-off and accuracy metrics. We show that this approach can identify up to about 90% of false positives, implying the planetary parameters encompass most of the relevant information contained in a light curve. Random Forest and Convolutional Neural Networks produce the highest accuracy and the best precision-recall trade-off. We also note that the accuracies as a function of the stellar eclipse flag SS have the best performance.

Link: Awaited

Title: AstroThink: Can Large Language Models Reason Their Way Through Astrophysics Olympiad Problems?

Authors: Ayan Bin Rafaih, Taner Shakir

Journal: Under peer-review at Artificial Intelligence Review

Year: 2025

Abstract:

State of the Art (SOTA) benchmarks and models exist for solving olympiad problems from many domains such as mathematics (IMO), informatics (IOI) and physics (IPhO). There are only some benchmarks available for the astrophysics domain, which only partially support astronomy. These efforts inculcate multiple choice questions and single-word answers, which often only test memory instead of conceptual understanding and breadth of knowledge. The International Olympiad of Astronomy and Astrophysics (IOAA) 2024 question paper includes problems that require in-depth thinking and robust conceptual foundations. We present a comprehensive evaluation of SOTA Large Language Models’ (LLMs) performance on the IOAA questions, using a two-fold validation scheme, encompassing both human annotators and LLM judges, along with a qualitative grading criteria to identify the most common points of failure in numerical calculations and reasoning steps. None of the chosen LLMs could achieve medal-level performance (top 50% or above percentile for scores, calculated from a reference score), and struggled significantly with the reasoning part of each problem. The best performance was achieved by DeepSeek-V3.1 with 44.83%. Hence, current LLMs are incapable of reasoning through astrophysics olympiad problems, since they suffer from logical errors, utilisation of irrelevant approaches, and contextual misunderstanding.

Link: Awaited

Title: Sustainability In Surgery: Problems, Solutions, And Recommendations

Authors: Ayan Bin Rafaih, Kaso Ari

Journal: Cureus

Year: 2025

Abstract:

The healthcare sector contributes significantly to global carbon emissions, with surgical care representing a substantial portion of this environmental impact. This review examines the environmental challenges associated with modern surgical practice, exploring issues related to operating room waste, energy consumption, pharmaceutical waste, and the use of single-use devices. We analyse current solutions being implemented across healthcare systems, including waste reduction strategies, energy-efficient practices, sustainable procurement, and circular economy approaches. Finally, evidence-based recommendations are provided for healthcare administrators, surgical teams, and policymakers to create more environmentally sustainable surgical practices while maintaining high standards of patient care. This article emphasizes that sustainable surgical practice is not only an environmental imperative but also presents opportunities for cost savings and improved healthcare delivery.

Link: PDF

Title: Comparing Surgical Outcomes Of Robotic And Laparoscopic Or Open Ileal Pouch–Anal Anastomosis: A Systematic Review And Meta-Analysis

Authors: Abdelrahman Abdelaal, Kaso Ari, Ayan Bin Rafaih, Ayaz Ahmed Memon, Irshad Shaikh

Journal: Journal of Robotic Surgery 

Year: 2025

Abstract:

Restorative proctocolectomy with ileal pouch-anal anastomosis (IPAA) is the standard surgical approach for patients with ulcerative colitis (UC) or familial adenomatous polyposis (FAP) seeking bowel continuity. While laparoscopy improves recovery, robotic-assisted surgery may offer advantages in pelvic procedures. However, its comparative efficacy remains unclear. This systematic review followed PRISMA guidelines to compare short-term outcomes of robotic-assisted IPAA with laparoscopic and open techniques. Literature was searched across PubMed, Embase, Web of Science, and the Cochrane Library for studies from January 2000 to June 2025. Included studies compared adult patients (≥ 18 years) undergoing IPAA for malignancy, UC or FAP. Primary outcomes were operative time, blood loss, hospital stay, and complications; secondary outcomes included conversion to open surgery, readmission, and reoperation. Meta-analysis was performed using pooled odds ratios, mean difference and 95% confidence intervals. Ten studies including 3,166 patients met inclusion criteria. Robotic IPAA was associated with a shorter length of stay (WMD – 1.1 days, 95% CI – 1.8 to – 0.3) and a non-significant trend toward fewer conversions to open surgery (OR 0.33, 95% CI 0.10-1.13). However, robotic procedures had longer operative times. Estimated blood loss did not differ significantly, and no significant differences were found in postoperative complications, anastomotic leaks, readmissions, or reoperations. Robotic-assisted IPAA is a safe and viable alternative to laparoscopic and open surgery, offering benefits in shorter hospital stay and conversion rates. Although operative times are longer, morbidity is comparable. Further prospective studies are needed to confirm these findings and evaluate long-term functional outcomes.

Link: PDF

Title: Robotic Beyond Total Mesorectal Excision (bTME) For Locally Advanced And Recurrent Anorectal Cancer – A Systematic Review 

Authors: Joachim Cheng En Ho, Aryan Raj Goel, Muriel Sirgi, Ayan Bin Rafaih, Ayaz Ahmed Memon, Irshad Shaikh

Journal: Journal of Robotic Surgery 

Year: 2025

Abstract:

Introduction: The surgical treatment for locally advanced or recurrent rectal cancer requires oncological clearance with a pelvic exenteration or a beyond total mesorectal excision (TME). The aim of this systematic review is to explore the safety and feasibility of robotic surgery in locally advanced and recurrent rectal cancer by evaluating perioperative outcomes, oncological clearance rates, and survival and recurrence rates postrobotic beyond TME surgery.

Methods: The systematic review will include studies published until the end of December 2023. The MEDLINE, EMBASE and Scopus databases will be searched. The screening process, study selection, data extraction, quality assessment and analysis will be performed by two independent reviewers. Discrepancies will be resolved by consensus with a third independent reviewer. The risk of bias will be assessed with validated scores. The primary outcomes will be oncological clearance, overall and disease-free survival, and local and systemic recurrence rates post robotic or robot-assisted beyond TME surgery for locally advanced or recurrent rectal cancer. Secondary outcomes will include perioperative outcomes.

Ethics and dissemination: No ethical approval is required for this systematic review as no individual patient cases are studied requiring access to individual medical records. The results of the systematic review will be disseminated with conference presentations and peer-reviewed paper publications.

Link: PDF

Title: Robotic Prosthetic Arm With 4 Degree Of Freedom Rotational Movement

Authors: Ayan Bin Rafaih

Journal: International Research Journal of Engineering and Technology

Year: 2025

Abstract:

This paper presents a cost-effective approach to developing a prosthetic robotic arm using Arduino-based components for individuals requiring upper limb rehabilitation. The high cost of commercial prosthetic devices makes them inaccessible to many patients, especially in low-income countries. To address this challenge, we propose a simplified 4 degree-of-freedom (DOF) robotic arm prototype that provides 180-degree rotational capability for basic daily tasks during the post-surgical recovery phase. The system utilizes an Arduino nano-microcontroller as the primary control unit, integrated with four servo motors arranged in a radial and lateral configuration to enable movement along four axes. Wireless communication is achieved through a HC-05 Bluetooth module, allowing virtual movement via an Android application with simple numerical commands. The robotic arm structure is fabricated using 3D-printed plastic components, significantly reducing manufacturing costs while maintaining functional integrity. The system operates through Pulse Width Modulation (PWM) signals with frequencies of 50 Hertz. Testing demonstrates successful execution of basic manipulation tasks including gripping, lifting and positioning objects within the operational workspace. This design offers a practical and affordable alternative for post-amputation rehabilitation, providing patients with essential motor functionality.

Link: PDF

Title: Exploring The Roles Of Extended Reality Technologies In Advancing Colorectal Surgical Training

Authors: Dominic Araszkiewicz, Taner Shakir, Gita Lingam, Ayan Bin Rafaih, Manish Chand

Journal: Frontline Gastroenterology

Year: 2025

Abstract:

Extended reality (XR) is an umbrella term for technologies that incorporate digital and physical elements to alter a user’s experience, namely: augmented reality (AR), virtual reality (VR) and mixed reality (MR). With National Health Service waiting lists at record levels, a shortage of trained endoscopists within the UK, and a greater likelihood of non-standard training outcomes following the COVID-19 pandemic, there is a requirement for significant developments in colorectal surgical training. AR has useful applications within both simulation training and intraoperative guidance, such as image overlays and conceptualisation. Both AR and VR offer three-dimensional reconstruction of radiological images, thereby allowing for enhanced appreciation and visualisation of anatomical structures. There is, however, a much greater evidence base for the validity of VR within the sphere of colorectal surgical training; primarily for simulation with respect to endoscopy, laparoscopy and robotics. MR is a developing field with technological advancements allowing for a combination of AR and VR. Potential advantages of XR teaching over conventional approaches include integration with artificial intelligence; objective assessments; immediate feedback; a wider exposure to pathologies and procedures and potential downstream safety benefits to patients. Environmental and socioeconomic factors require further evaluation, with the potential for meta-conferences or meta-hospitals. Disadvantages may include a lack of focus on patient communication skills and the lack of standardised XR training protocols. These technologies have an exciting future in serving as adjuncts to colorectal surgical training.

Link: PDF

Title: Gyro Sensor Based Smart Helmet For Automated Early Accident Detection

Authors: Ayan Bin Rafaih

Journal: International Research Journal of Engineering and Technology

Year: 2025

Abstract:

The number of worldwide motorcycle accidents is increasing every year, which necessitates the need of safety procedures such as wearing helmets. The integration of Internet of Things (IoT), Artificial Intelligence (AI), Automated Detection and Machine Learning (ML) into this field has improved safety and efficiency, with the help of smart helmets. Our approach proposes an Arduino-based helmet that provides early accident-detection through the use of a gyro sensor to measure the accelerations in all directions. This system continuously monitors for any variations from the gyro offsets and the upper and lower thresholds defined for each direction (x, y and z): a positive detection would lead to the GSM module connecting to a pre-defined SIM network, along with the GPS module for location coordinates, to send a message to the user’s emergency contact as soon as the accident is detected. Thus, the message would act as an early warning system that would also include the map latitude and longitude coordinates. This setup provides high accuracy and precision, with constant monitoring of the angular velocities at a set frequency.

Link: PDF

Title: Artificial Intelligence Driven Approaches To Managing Surgeon Fatigue And Improving Performance

Authors: Ayan Bin Rafaih, Kaso Ari

Journal: Cureus

Year: 2024

Abstract:

Surgeon fatigue significantly affects cognitive and motor functions, increasing the risk of errors and adverse patient outcomes. Traditional fatigue management methods, such as structured breaks and duty-hour limits, are insufficient for real-time fatigue detection in high-stakes surgeries. With advancements in artificial intelligence (AI), there is growing potential for AI-driven technologies to address this issue through continuous monitoring and adaptive interventions. This paper explores how AI, via machine learning algorithms, wearable devices, and real-time feedback systems, enables comprehensive fatigue detection by analysing physiological, behavioural, and environmental data. Techniques such as heart rate variability analysis, electroencephalogram monitoring, and computer vision-based behavioural analysis are examined, as well as predictive models that provide proactive solutions. These AI-driven systems could suggest personalized break schedules, task redistribution, and interface adaptations in response to real-time fatigue indicators, potentially enhancing surgical safety and precision. However, ethical challenges, including data privacy and surgeon autonomy, must be carefully navigated to foster acceptance and integration within clinical settings. This review highlights AI’s transformative potential in optimizing fatigue management and improving overall outcomes in the operating room​​​​​.

Link: PDF