[Shabelle] Mogadishu, Somalia -- The National Intelligence and Security Agency (NISA) of Somalia announced on Thursday the arrest of two men with ties to the militant group Al-Shabaab in the capital city of Mogadishu.

[Shabelle] Mogadishu -- Somalia's National Intelligence and Security Agency (NISA) conducted a targeted operation in the Dharaarweyn area near Galcad city, within the Galgaduud region.

Artificial intelligence has more in common with ants than humans, says Neil Lawrence. Only by taking a more nuanced view of intelligence can we see how machines will truly transform society

Artificial Intelligence (AI) is poised to revolutionize family medicine, offering a transformative approach to achieving the Quintuple Aim. This article examines the imperative for family medicine to adapt to the rapidly evolving field of AI, with an emphasis on its integration in clinical practice. AI's recent advancements have the potential to significantly transform health care. We argue for the proactive engagement of family medicine in directing AI technologies toward enhancing the "Quintuple Aim."

The article highlights potential benefits of AI, such as improved patient outcomes through enhanced diagnostic tools, clinician well-being through reduced administrative burdens, and the promotion of health equity by analyzing diverse data sets. However, we also acknowledge the risks associated with AI, including the potential for automation to diverge from patient-centered care and exacerbate health care disparities. Our recommendations stress the need for family medicine education to incorporate AI literacy, the development of a collaborative for AI integration, and the establishment of guidelines and standards through interdisciplinary cooperation. We conclude that although AI poses challenges, its responsible and ethical implementation can revolutionize family medicine, optimizing patient care and enhancing the role of clinicians in a technology-driven future.

Artificial intelligence (AI) is certainly going to have a large, potentially huge, impact on the practice of family medicine. The specialty is fortunate to have leading experts in the field to guide us along the way. One such team of forward thinkers provides insights into where AI can take the specialty. Another article reports on how well AI performed on the American Board of Family Medicine In-Training Examination. In addition to AI, we have 3 articles that investigate the intersection of social needs and the practice of medicine. Four clinical review articles cover nonalcoholic fatty liver disease, headache treatments, single maintenance and reliever therapy for asthma, and the use of cannabis in the setting of chronic pain. The clinical research articles cover point-of-care hemoglobin A1c testing, continuous glucose monitoring, and screening for HIV. Another group of articles examines the profession of family medicine, covering topics ranging from how women family physicians negotiate their first jobs to the words we use to define primary care.

The pursuit of harnessing data for knowledge creation has been an enduring quest, with the advent of machine learning (ML) and artificial intelligence (AI) marking significant milestones in this journey. ML, a subset of AI, emerged as the practice of employing mathematical models to enable computers to learn and improve autonomously based on their experiences. In the pharmaceutical and biopharmaceutical sectors, a significant portion of manufacturing data remains untapped or insufficient for practical use. Recognizing the potential advantages of leveraging the available data for process design and optimization, manufacturers face the daunting challenge of data utilization. Diverse proprietary data formats and parallel data generation systems compound the complexity. The transition to Pharma 4.0 necessitates a paradigm shift in data capture, storage, and accessibility for manufacturing and process operations. This paper highlights the pivotal role of AI in converting process data into actionable knowledge to support critical functions throughout the whole product life cycle. Furthermore, it underscores the importance of maintaining compliance with data integrity guidelines, as mandated by regulatory bodies globally. Embracing AI-driven transformations is a crucial step toward shaping the future of the pharmaceutical industry, ensuring its competitiveness and resilience in an evolving landscape.

The aim of this study was to validate a previously developed deep learning model in 5 independent clinical trials. The predictive performance of this model was compared with the international prognostic index (IPI) and 2 models incorporating radiomic PET/CT features (clinical PET and PET models). Methods: In total, 1,132 diffuse large B-cell lymphoma patients were included: 296 for training and 836 for external validation. The primary outcome was 2-y time to progression. The deep learning model was trained on maximum-intensity projections from PET/CT scans. The clinical PET model included metabolic tumor volume, maximum distance from the bulkiest lesion to another lesion, SUV_peak, age, and performance status. The PET model included metabolic tumor volume, maximum distance from the bulkiest lesion to another lesion, and SUV_peak. Model performance was assessed using the area under the curve (AUC) and Kaplan–Meier curves. Results: The IPI yielded an AUC of 0.60 on all external data. The deep learning model yielded a significantly higher AUC of 0.66 (P < 0.01). For each individual clinical trial, the model was consistently better than IPI. Radiomic model AUCs remained higher for all clinical trials. The deep learning and clinical PET models showed equivalent performance (AUC, 0.69; P > 0.05). The PET model yielded the highest AUC of all models (AUC, 0.71; P < 0.05). Conclusion: The deep learning model predicted outcome in all trials with a higher performance than IPI and better survival curve separation. This model can predict treatment outcome in diffuse large B-cell lymphoma without tumor delineation but at the cost of a lower prognostic performance than with radiomics.

BACKGROUND AND PURPOSE:

Intracranial vessel wall imaging is technically challenging to implement, given the simultaneous requirements of high spatial resolution, excellent blood and CSF signal suppression, and clinically acceptable gradient times. Herein, we present our preliminary findings on the evaluation of a deep learning–optimized sequence using T1-weighted imaging.

BACKGROUND AND PURPOSE:

Recently, artificial intelligence tools have been deployed with increasing speed in educational and clinical settings. However, the use of artificial intelligence by trainees across different levels of experience has not been well-studied. This study investigates the impact of artificial intelligence assistance on the diagnostic accuracy for intracranial hemorrhage and large-vessel occlusion by medical students and resident trainees.

A new report by the global union Education International shows that AI can degrade the quality of education, worsen working conditions for teachers and provide inferior schooling for students.

The post Artificial Intelligence can cause fake education appeared first on rabble.ca.

Artificial intelligence has more in common with ants than humans, says Neil Lawrence. Only by taking a more nuanced view of intelligence can we see how machines will truly transform society

As artificial intelligence becomes more common in university classrooms, some professors are weighing the benefits — and downsides — of students using it for research projects.

People keep predicting that each wave of new technology will mean humans can put their feet up. It hasn't happened yet. Some economists and anthropologists who study the subject say even with the arrival of artificial intelligence, humans will remain integral to making the world go round.

President-elect Donald Trump announced Tuesday that John Ratcliffe, a former Texas congressman and director of national intelligence, will serve as the director of the Central Intelligence Agency in his administration.

I've spent a week with Apple Intelligence—here are the takeaways.

Anthropic’s smallest AI model now beats its older largest LLM, Opus, at some tasks.

By Peter Tummino, CSO of Nimbus Therapeutics, as part of the From The Trenches feature of LifeSciVC  “Over the next five to 10 years, our goal is to become a company that’s leading the world in personalized medicines, a company

The post Medicinal Chemistry In The Age Of Artificial Intelligence appeared first on LifeSciVC.

By fostering collaboration and seamless data integration into healthcare systems, the industry is laying the groundwork for a future in which “personalized medicine” is so commonplace within clinical practice that we will just start calling it “medicine.”

The post Driving Genetic Testing Adoption and Improved Patient Care through Health Data Intelligence appeared first on MedCity News.

Apr 18, 2024

The human tragedy continuing to unfold in Gaza and Israel reminds us how important it is to get strategic forecasting right. While in no way excusing Hamas’ culpability for 7 October, we also cannot dismiss the fact that the failure to anticipate and prepare for such an attack has had grave consequences for communities on both sides of this conflict, undermined efforts to bring peace and prosperity to the region, and affected global interests through the expansion of the conflict to the Red Sea and potentially beyond. 

A new method of manufacturing dental crowns using generative medlinkartificial intelligence/medlink (AI) was developed by researchers from the Faculty

An medlinkartificial intelligence/medlink (AI) platform developed by the University of Surrey, in partnership with King's College London, Royal Surrey

Artificial intelligence tool for detecting skin cancer, which has outperformed existing methods in identifying suspicious lesions has been developed by scientists in the East of England (!--ref1--).

Dry Eye Disease (DED) is a prevalent ocular condition, impacting as many as 30% of individuals worldwide. Its onset can significantly impede the medlinkquality

Researchers have crafted an medlinkartificial intelligence (AI)/medlink model capable of discerning the optimal drug combination and timing for treating a bacterial infection.

medlinkArtificial Intelligence (AI)/medlink holds the potential for providing psychological first aid to address India's growing mental health concerns,

According to health experts, medlinkartificial intelligence/medlink (AI) is advancing cancer treatment, enhancing traditional methods like medlinkchemotherapy/medlink,

By harnessing medlinkartificial intelligence/medlink (AI) to assess retinal images, an international team aims to enhance medlinkcardiovascular

As artificial intelligence (AI) tools become more integrated into health care, recent research by Lucia Vitale, a doctoral candidate in the Politics Department

Climate change-fueled extreme weather, like devastating floods and prolonged droughts, frequently triggers outbreaks of diarrheal diseases, especially

Practicing Transcendental meditation may boost your emotional intelligence and relieve stress levels when you are at work finds a new study. Finding

Artificial Intelligence (AI) proves as an inevitable tool in achieving Sustainable Development Goals (SDGs - 17 interlinked global goals for a better

In this week’s episode of the Hotel Moment podcast, Bryson Koehler, Revinate CEO, guest hosts to interview Jeff Jonas, Founder, CEO, and Chief Scientist of Senzing. Jeff paints two pictures — one in which hoteliers practice responsible data management and another in which hoteliers fail to make intelligent decisions because of disorganized and inaccurate data. Identity resolution is one of the most important tools Jeff believes every tech stack should have to manage their data, understand guest profiles with accuracy, and execute data-powered marketing initiatives.

In the ever-evolving hospitality industry, the use of business intelligence is becoming increasingly important. Hoteliers are recognizing the immense value that data brings to their business, from understanding drivers of demand to developing effective revenue management strategies. But the big question is – how willing are they to invest in new technology?

Business Intelligence (BI) is much more democratic over the last decade. BI is no longer reserved only for senior management decision makers, responsible for strategic and tactical business decisions. The BI is increasingly...