Expert Systems

Judge extends block on Trump birth control rules across US

BBC News

A US federal judge has blocked new Trump administration regulations on birth control from applying across the entire country. The rules allow employers and insurers to decline to provide birth control if doing so violates their "religious beliefs" or "moral convictions". The rules were to come into effect nationwide from Monday. But the judge in Philadelphia granted an injunction requested by attorneys general in Pennsylvania and New Jersey. Judge Wendy Beetlestone ruled that the new rules would make it more difficult for many women to obtain free contraception and would be an undue burden on US states.

The Latest: Official Decries Blocking of Birth Control Rules

U.S. News

A federal health official says a nationwide injunction on new Trump administration rules that allowed more employers to opt out of providing women with no-cost birth control will force Americans to "violate" their consciences.

Second U.S. Judge Blocks Trump Administration Birth Control Rules

U.S. News

U.S. District Judge Wendy Beetlestone in Philadelphia issued a nationwide injunction preventing the rules from taking effect, a day after another judge issued a more limited ruling blocking their enforcement in 13 states and the District of Columbia.

U.S. Judge Partially Blocks Trump Administration Birth Control Rules

U.S. News

U.S. District Judge Haywood Gilliam in Oakland granted a request by 14 Democratic attorneys general for a preliminary injunction. The rules, which are set to go into effect Jan. 14, allow businesses or nonprofits to obtain exemptions to an Obamacare requirement for contraceptive coverage on moral or religious grounds.

AI Beats Expert Doctors at Finding Cervical Pre-Cancers - PC Tech Magazine


Artificial Intelligence (AI) may be poised to wipe out cervical cancer, after a study showed on Thursday computer algorithms can detect pre-cancerous lesions far better than trained experts or conventional screening tests. According to the World Health Organization (WHO), cervical cancer is the fourth most frequent cancer in women with an estimated 570,000 new cases globally in 2018. Despite major advances in screening and vaccination, which can prevent the spread of human papillomavirus which causes most cases of cervical cancer, those gains have mainly benefited women in rich nations. Some 266,000 women died of cervical cancer globally in 2012, 90% of them in low-and middle-income nations, according to the WHO. "Cervical cancer is now a disease of poverty, of low resources," said senior author Mark Schiffman, a doctor at the National Cancer Institute's Division of Cancer Epidemiology and Genetics near Washington who has been searching for a cure to cervical cancer for 35 years.

California Heads to Court to Fight Trump Birth Control Rules

U.S. News

Judge Haywood Gilliam previously blocked an interim version of those rules -- a decision that was upheld in December by an appeals court. But the case is before him again after the administration finalized the measures in November, prompting a renewed legal challenge by California and other states.

Artificial Intelligence – An expert system in ener…


I intend to develop an expert system in energy sector. I have enough expertise in this domanin and I'm lookin for a shell to build such project and,

Microsoft open sources the inference engine at the heart of its Windows machine-learning platform


Microsoft is using its annual Connect(); developers conference to make a number of AI-related announcements, including the open sourcing of one of its key pieces of its Windows Machine Learning (Windows ML) platform. Microsoft is open sourcing the Open Neural Network Exchange (ONNX) runtime, officials said today, December 4. The ONNX runtime is an inference engine for machine-learning models in the ONNX format. Microsoft is making it available on GitHub so developers can customize and integrate the runtime into their existing systems and compile/build it on a variety of operating systems. The ONNX engine is a key piece of Windows ML. Microsoft is building this machine-learning interface into Windows 10 to try to get developers to use trained machine learning models in their Windows apps.

Fuzzy expert system for prediction of prostate cancer Artificial Intelligence

A fuzzy expert system (FES) for the prediction of prostate cancer (PC) is prescribed in this article. Age, prostate-specific antigen (PSA), prostate volume (PV) and $\%$ Free PSA ($\%$FPSA) are fed as inputs into the FES and prostate cancer risk (PCR) is obtained as the output. Using knowledge based rules in Mamdani type inference method the output is calculated. If PCR $\ge 50\%$, then the patient shall be advised to go for a biopsy test for confirmation. The efficacy of the designed FES is tested against a clinical data set. The true prediction for all the patients turns out to be $68.91\%$ whereas only for positive biopsy cases it rises to $73.77\%$. This simple yet effective FES can be used as supportive tool for decision making in medical diagnosis.

A rule-based system proposal to aid in the evaluation and decision-making in external beam radiation treatment planning Artificial Intelligence

As part of a plan launched by the Ministry of Health of Brazil to increase the availability of linear accelerators for radiotherapy treatment for the whole country, for which Varian Medical Systems company has won the bidding, a technical cooperation agreement was signed inviting Brazilian Scientific and Technological Institutions to participate in a technology transfer program. As a result, jointly, the Eldorado Research Institute and the Center for Biomedical Engineering of the University of Campinas presents in this work, the concepts behind of a proposed rule engine to aid in the evaluation and decision-making in radiotherapy treatment planning. Normally, the determination of the radiation dose for a given patient is a complex and intensive procedure, which requires a lot of domain knowledge and subjective experience from the oncologists' team. In order to help them in this complex task, and additionally, provide an auxiliary tool for less experienced oncologists, it is presented a project conception of a software system that will make use of a hybrid data-oriented approach. The proposed rule engine will apply both inference mechanism and expression evaluation to verify and accredit the quality of an external beam radiation treatment plan by considering, at first, the 3D-conformal radiotherapy (3DCRT) technique.