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New Tech Allows Faster Breast Cancer Detection In Middle East

Breast cancer is the most common form of the disease for women in the Arab world. But now, AI screening solutions, precision medicine and molecular imaging are fighting back.

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An estimated 2.26 million women worldwide are diagnosed with breast cancer each year. In the Arab world, nearly 20% of all new cases turn out to be breast cancer, making this form of the disease the most common for women in the region.

To tackle this problem, several medical tech companies have developed screening tests to avoid misdiagnosis and late diagnosis. From AI to 3D imaging, each solution strives to improve the screening process, making it more accessible and affordable to Middle Eastern patients.

Early Detection Improvements

Mammogram diagnostics have evolved dramatically over the years. 3D scanning allows oncologists to detect small masses in dense breast tissue much earlier than traditional imaging tools allow.

“Using 3D mammograms, we can see lumps hidden within breasts accurately. By limiting the effect of covering the breast tissue, 3D mammography can make tumor detection easier. Looking into various pictures has helped specialists discover a larger number of cancer growths which was not possible with 2D scans,” says Dr. Timor Al-Shee, Surgical Consultant of Breast Oncology, King Faisal Specialist Hospital and Research Center, Saudi Arabia.

Despite their advancements, 3D mammograms are costly and still risk the possibility of false-positive results. To minimize unnecessary biopsies and increase the accuracy of decisions, researchers from New York University and NYU Abu Dhabi have devised a method to identify cancers using AI.

Devised by a team led by Farah Shamout, Yiqiu Shen and Jamie Oliver, the AI tool offers “radiologist-level accuracy” and promises to improve the consistency and efficiency of ultrasound diagnosis.

So far, the findings have been promising, with AI able to play a complementary role as a decision-making tool during the early stages of screening, aiding clinicians when forming a diagnosis.

Genetic Testing And Molecular Imaging

As well as 3D imaging and AI, genetic testing can also achieve reliable and accurate results. Although most breast cancers are not thought to be caused by inherited mutations, the tests can be helpful for women with a family history of breast cancer.

“The UAE uses the latest technologies to drive innovation in healthcare. We are part of the DoH-led Personalized Precision Medicine Programme for oncology in the region that specifically targets breast cancer. The treatment is based on a patient’s genetic makeup and genetic changes in cancer cells,” says Dr. Fahed Al Marzooqi, COO of G42 Healthcare.

Molecular breast imaging, on the other hand, can be used alongside a mammogram and involves a radioactive tracer with a nuclear medicine scanner. The tracer is injected into a vein, and if cancer cells are detected, the tracer will light up.

As well as helping to diagnose cancers earlier, these new technologies could also be used to tailor precision medicines for treatment. Scientists already know that breast cancer is treatable if spotted early, so it seems that the future of cancer medicines is all about evaluation — from genes and environment to lifestyle factors. Meanwhile, technological advances are beginning to allow oncologists to tailor highly individual treatment plans for patients.

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NVIDIA Puts GPT-5.5 Codex In Hands Of 10,000 Staff

The chipmaker has significantly expanded OpenAI’s latest model across teams from engineering to HR under tight internal controls.

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NVIDIA has started rolling out OpenAI’s GPT-5.5 model through the Codex coding agent to more than 10,000 employees, extending the tool well beyond software teams and into core business functions.

The deployment covers engineering, product, legal, marketing, finance, sales, HR, operations and developer programs. Staff are using Codex for coding, internal research and routine knowledge work as companies test whether AI agents can move from demos to daily use.

GPT-5.5 is running on NVIDIA’s GB200 NVL72 rack-scale systems, linking OpenAI’s newest model directly to the chipmaker’s latest infrastructure push. NVIDIA said the systems cut cost per million tokens by 35 times and raise token output per second per megawatt by 50 times versus earlier generations.

openai's new gpt-5.5 powers codex on nvidia infrastructure 2

Inside the company, it says the effects are immediate. Debugging work that once took days is being finished in hours and experiments across large codebases that used to stretch over weeks are now handled overnight. Teams are also building features from natural-language prompts with fewer failed runs.

In a company-wide note urging staff to adopt the tool, CEO Jensen Huang wrote: “Let’s jump to lightspeed. Welcome to the age of AI.”

Security remains central to the rollout. Codex can connect through Secure Shell to approved cloud virtual machines, allowing agents to work with company data without moving it outside approved environments. NVIDIA said it assigned cloud VMs to employees so agents run in isolated sandboxes with full audit trails.

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The company added that the setup uses a zero-data-retention policy. Access to production systems is read-only through command-line tools and internal automation layers.

The move also highlights NVIDIA’s long relationship with OpenAI. NVIDIA said the partnership began in 2016, when Huang personally delivered the first DGX-1 AI supercomputer to OpenAI’s San Francisco office.

The two companies have since worked across hardware and model deployment. NVIDIA also said OpenAI plans to deploy more than 10 gigawatts of NVIDIA systems for future AI infrastructure.

For Gulf markets pouring money into sovereign AI and enterprise automation, the signal is clear: internal AI agents are moving from pilot phase to standard tooling.

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